Performance information

• Reinforcement learning-based autonomous driving control for efficient road utilization in lane-less environments　　　　　　　　　　　　　　　
  Mao Tobisawa; Kenji Matsuda; Tenta Suzuki; Tomohiro Harada; Junya Hoshino; Yuki Itoh; Kaito Kumagae; Johei Matsuoka; Kiyohiko Hattori
  Artificial Life and Robotics, Mar. 2025, [Reviewed]
  English, Scientific journal
  DOI：https://doi.org/10.1007/s10015-025-01013-5
  DOI ID：10.1007/s10015-025-01013-5
• 進化計算とガウス過程回帰を用いた制約付き最適化問題における制約緩和による最適解改善予測　　　　　　　　　　　　　　　
  名畑駿都; 原田智広
  First page：185, Last page：194, Mar. 2025, [Last]
  Japanese, Symposium
  共同研究・競争的資金等ID：47716797
• 理想点の早期伝搬と通信効率を考慮したネットワーク構造を用いる並列多目的進化計算　　　　　　　　　　　　　　　
  原田大輝; 原田智広
  First page：34, Last page：41, Mar. 2025, [Last]
  Japanese, Symposium
• 深層強化学習を用いた協調自動運転制御に対するデータ拡張による汎化性能向上　　　　　　　　　　　　　　　
  中谷 玲雄; 原田 智広; 三浦 幸也; 服部 聖彦; 松岡 丈平
  First page：20, Last page：25, Mar. 2025, [Corresponding]
  Japanese, Symposium
• Fast implementation of extreme learning machine-based directRanker for surrogate-assisted evolutionary algorithms　　　　　　　　　　　　　　　
  Tomohiro Harada
  Evolutionary Intelligence, Volume：18, Number：1, Feb. 2025, [Reviewed], [Lead, Last, Corresponding]
  Surrogate-assisted evolutionary algorithms (SAEAs) have been widely used to solve computationally expensive optimization problems. The extreme learning machine-based DirectRanker (ELDR) is a single-layer feed-forward neural network surrogate model designed for SAEAs. ELDR estimates the superiority of two solutions with a high estimation accuracy, even in high-dimensional problems. However, ELDR requires a long computation time as the problem dimensionality and the number of hidden neurons increase, thus making it difficult to apply it to high-dimensional problems. A surrogate model should be computationally efficient and enable rapid fitness estimations. Therefore, this paper proposes a fast implementation technique, i.e., fast version ELDR (fELDR) that achieves mathematically equivalent learning results with low computational complexity. Additionally, this paper proposes a pointwise score function to render the prediction results reusable. The experimental results confirmed the effectiveness of fELDR when compared with the original ELDR. The learning results of the proposed fELDR were equivalent to those of the original ELDR while reducing the training time by up to 97%, especially when using a large hidden layer on a high dimensionality problem. Moreover, due to the reusable prediction results, the computation time of the fELDR-assisted SAEA can be further decreased by 79.5% when compared with that of the original ELDR-assisted SAEA. The reduced training time and reusable prediction results of fELDR render it feasible to apply ELDR to high-dimensional optimization problems and realize a high prediction accuracy with a large number of hidden neurons.
  English, Scientific journal
  DOI：https://doi.org/10.1007/s12065-024-01005-7
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85213028020&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85213028020&origin=inward
  DOI ID：10.1007/s12065-024-01005-7, ISSN：1864-5909, eISSN：1864-5917, SCOPUS ID：85213028020, 共同研究・競争的資金等ID：32553614
• Optimization of Vehicle Collision Avoidance Behavior by Variable Directional Sensor Control Using Reinforcement Learning　　　　　　　　　　　　　　　
  Kaito Kumagae; Mao Tobisawa; Kenji Matsuda; Tenta Suzuki; Junya Hoshino; Yuki Itoh; Johei Matsuoka; Tomohiro Harada; Kiyohiko Hattori
  The Joint Symposium: 30th International Symposium on Artificial Life and Robotics and 10th International Symposium on BioComplexity (AROB-ISBC 2025), First page：113, Last page：118, Jan. 2025, [Reviewed]
  English, International conference proceedings
• Reinforcement Learning-based Autonomous Driving Control for Efficient Road Utilization in Lane-less Environments　　　　　　　　　　　　　　　
  Mao Tobisawa; Kenji Matsuda; Tenta Suzuki; Junya Hoshino; Yuki Itoh; Kaito Kumagae; Johei Matsuoka; Tomohiro Harada; Kiyohiko Hattori
  The Joint Symposium: 30th International Symposium on Artificial Life and Robotics and 10th International Symposium on BioComplexity (AROB-ISBC 2025), First page：1039, Last page：1046, Jan. 2025, [Reviewed]
  English, International conference proceedings
• Deep Reinforcement Learning Method Considering Vehicle Sizes for Cooperative Autonomous Driving　　　　　　　　　　　　　　　
  Akito Takenaka; Yukiya Miura; Tomohiro Harada; Kiyohiko Hattori; Johei Matsuoka
  The Joint Symposium: 30th International Symposium on Artificial Life and Robotics and 10th International Symposium on BioComplexity (AROB-ISBC 2025), First page：770, Last page：775, Jan. 2025, [Reviewed]
  English, International conference proceedings
• Automatic Space Design Adapted to Swarm Robot Movement　　　　　　　　　　　　　　　
  Junya Hoshino; Yuki Itoh; Tenta Suzuki; Kenji Matsuda; Kaito Kumagae; Mao Tobisawa; Tomohiro Harada; Johei Matsuoka; Kiyohiko Hattori
  Fourteenth International Conference on Swarm Intelligence (ANTS 2024), Oct. 2024, [Reviewed]
  English, International conference proceedings
• Automated Vehicle Approach to Traffic Control Using Reinforcement Learning - Influence of Map Information on Intersection Passage　　　　　　　　　　　　　　　
  Kenji Matsuda; Tenta Suzuki; Tomohiro Harada; Johei Matsuoka; Mao Tobisawa; Jyunya Hoshino; Yuki Itoh; Kaito Kumagae; Kiyohiko Hattori
  Fourteenth International Conference on Swarm Intelligence (ANTS 2024), Oct. 2024, [Reviewed]
  English, International conference proceedings
• Developing Flexible Tile-Independent Simulation Environments for Cooperative Autonomous Vehicle Control via Deep Reinforcement Learning on Lane-Less Roads　　　　　　　　　　　　　　　
  Reo Nakaya; Tomohiro Harada; Yukiya Miura; Kiyohiko Hattori; Johei Matsuoka
  SICE Festival 2024 with Annual Conference (SICE FES 2024), First page：576, Last page：579, Aug. 2024, [Reviewed]
  English, International conference proceedings
• Switching Constraint Handling Evolutionary Algorithm for Constrained Multi-modal Multi-objective Optimization Problems　　　　　　　　　　　　　　　
  Yuhirio Ono; Tomohiro Harada; Yukiya Miura
  SICE Festival 2024 with Annual Conference (SICE FES 2024), First page：1079, Last page：1084, Aug. 2024, [Reviewed]
  English, International conference proceedings
• Report on Open Space Discussion 2023　　　　　　　　　　　　　　　
  Tomohiro Harada; Takato Kinoshita; Hiroki Shiraishi; Ryo Takano; Yusuke Tajima; Yuki Tanigaki; Nobuo Namura; Kei Nishihara
  Transaction of the Japanese Society for Evolutionary Computation, Volume：15, Number：1, First page：11, Last page：19, Jul. 2024, [Reviewed], [Invited], [Lead, Corresponding]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.15.11
  DOI ID：10.11394/tjpnsec.15.11
• Cooperative Autonomous Driving Control among Vehicles of Different Sizes Using Deep Reinforcement Learning
  Akito Takenaka; Tomohiro Harada; Yukiya Miura; Kiyohiko Hattori; Johei Matuoka
  2024 International Joint Conference on Neural Networks (IJCNN), First page：1, Last page：8, Jun. 2024, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/ijcnn60899.2024.10649971
  DOI ID：10.1109/ijcnn60899.2024.10649971
• Energy and Quality of Surrogate-Assisted Search Algorithms: a First Analysis　　　　　　　　　　　　　　　
  Tomohiro Harada; Enrique Alba; Gabriel Luque
  2024 IEEE Congress on Evolutionary Computation (CEC), Volume：35, First page：1, Last page：8, Jun. 2024, [Reviewed], [Lead, Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/cec60901.2024.10611758
  DOI ID：10.1109/cec60901.2024.10611758, DBLP ID：conf/cec/Harada0L24
• Analysis of the Impact of Prediction Accuracy on Search Performance in Surrogate-assisted Evolutionary Algorithms　　　　　　　　　　　　　　　
  Yuki Hanawa; Tomohiro Harada; Yukiya Miura
  2024 IEEE Congress on Evolutionary Computation (CEC), Volume：1, First page：1, Last page：8, Jun. 2024, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/cec60901.2024.10611759
  DOI ID：10.1109/cec60901.2024.10611759, DBLP ID：conf/cec/HanawaHM24
• Acquisition of Cooperative Control of Multiple Vehicles Through Reinforcement Learning Utilizing Vehicle-to-Vehicle Communication and Map Information
  Tenta Suzuki; Kenji Matsuda; Kaito Kumagae; Mao Tobisawa; Junya Hoshino; Yuki Itoh; Tomohiro Harada; Jyouhei Matsuoka; Toshinori Kagawa; Kiyohiko Hattori
  Journal of Robotics and Mechatronics, Volume：36, Number：3, First page：642, Last page：657, Jun. 2024, [Reviewed]
  In recent years, extensive research has been conducted on the practical applications of autonomous driving. Much of this research relies on existing road infrastructure and aims to replace and automate human drivers. Concurrently, studies on zero-based control optimization focus on the effective use of road resources without assuming the presence of car lanes. These studies often overlook the physical constraints of vehicles in their control optimization based on reinforcement learning, leading to the learning of unrealistic control behaviors while simplifying the implementation of ranging sensors and vehicle-to-vehicle communication. Additionally, these studies do not use map information, which is widely employed in autonomous driving research. To address these issues, we constructed a simulation environment that incorporates physics simulations, realistically implements ranging sensors and vehicle-to-vehicle communication, and actively employs map information. Using this environment, we evaluated the effect of vehicle-to-vehicle communication and map information on vehicle control learning. Our experimental results show that vehicle-to-vehicle communication reduces collisions, while the use of map information improves the average vehicle speed and reduces the average lap time.
  Fuji Technology Press Ltd., English, Scientific journal
  DOI：https://doi.org/10.20965/jrm.2024.p0642
  DOI ID：10.20965/jrm.2024.p0642, ISSN：0915-3942, eISSN：1883-8049
• Automatic Route Design by Stepwise Subdivision of Virtual Walls —Reduces Route Length and Speeds Up Execution Time—
  Yuki Itoh; Junya Hoshino; Tenta Suzuki; Kenji Matsuda; Kaito Kumagae; Mao Tobisawa; Tomohiro Harada; Jyouhei Matsuoka; Toshinori Kagawa; Kiyohiko Hattori
  Journal of Robotics and Mechatronics, Volume：36, Number：3, First page：628, Last page：641, Jun. 2024, [Reviewed]
  With the development of autonomous driving technology utilizing machine learning, AI, and sensors, research on autonomous driving control has become more active, and a large number of innovative studies are underway. In the near future, all autonomous vehicle fleets will be able to communicate with each other for sharing information and overall optimal traffic control will be achieved. One of the vehicle control systems that are based on the premise of such a fully automated society is the “signal-less intersection.” There is an intersection traffic control method that achieves safe and rational route selection by using virtual walls (VWs), which are virtual obstacles, but there are issues in terms of total route length and reduction of computation time. To address the issues, we propose a method that (1) prunes unneeded paths and (2) arranges VWs in a stepwise manner. The effectiveness of the proposed method was evaluated by simulation, and the results showed that the total route length and execution time were reduced.
  Fuji Technology Press Ltd., English, Scientific journal
  DOI：https://doi.org/10.20965/jrm.2024.p0628
  DOI ID：10.20965/jrm.2024.p0628, ISSN：0915-3942, eISSN：1883-8049
• Interchange flow control with dynamic obstacles optimized using genetic algorithms—a concept of virtual walls
  Junya Hoshino; Yuki Itoh; Ryuma Saotome; Tomohiro Harada; Kenji Matsuda; Tenta Suzuki; Mao Tobisawa; Kaito Kumagae; Johei Matsuoka; Toshinori Kagawa; Kiyohiko Hattori
  Artificial Life and Robotics, Volume：29, Number：2, First page：230, Last page：241, Apr. 2024, [Reviewed]
  Springer Science and Business Media LLC, English, Scientific journal
  DOI：https://doi.org/10.1007/s10015-024-00946-7
  DOI ID：10.1007/s10015-024-00946-7, ISSN：1433-5298, eISSN：1614-7456
• Hierarchical Reward Model of Deep Reinforcement Learning for Enhancing Cooperative Behavior in Automated Driving
  Kenji Matsuda; Tenta Suzuki; Tomohiro Harada; Johei Matsuoka; Mao Tobisawa; Jyunya Hoshino; Yuuki Itoh; Kaito Kumagae; Toshinori Kagawa; Kiyohiko Hattori
  Journal of Advanced Computational Intelligence and Intelligent Informatics, Volume：28, Number：2, First page：431, Last page：443, Mar. 2024, [Reviewed]
  In recent years, studies on practical application of automated driving have been conducted extensively. Most of the research assumes the existing road infrastructure and aims to replace human driving. There have also been studies that use reinforcement learning to optimize car control from a zero-based perspective in an environment without lanes, one of the existing types of road. In those studies, search and behavior acquisition using reinforcement learning has resulted in efficient driving control in an unknown environment. However, the throughput has not been high, while the crash rate has. To address this issue, this study proposes a hierarchical reward model that uses both individual and common rewards for reinforcement learning in order to achieve efficient driving control in a road, we assume environments of one-way, lane-less, automobile-only. Automated driving control is trained using a hierarchical reward model and evaluated through physical simulations. The results show that a reduction in crash rate and an improvement in throughput is attained by increasing the number of behaviors in which faster cars actively overtake slower ones.
  Fuji Technology Press Ltd., English, Scientific journal
  DOI：https://doi.org/10.20965/jaciii.2024.p0431
  DOI ID：10.20965/jaciii.2024.p0431, ISSN：1343-0130, eISSN：1883-8014, ORCID：155808807
• Parallel cooperative multiobjective coevolutionary algorithm for constrained multiobjective optimization problems　　　　　　　　　　　　　　　
  Tomohiro Harada
  Applied Soft Computing, Volume：153, First page：111290, Last page：111290, Mar. 2024, [Reviewed], [Lead, Last, Corresponding]
  Elsevier BV, English, Scientific journal
  DOI：https://doi.org/10.1016/j.asoc.2024.111290
  DOI ID：10.1016/j.asoc.2024.111290, ISSN：1568-4946, ORCID：151180911
• 大規模言語モデル駆動の最適化ベンチマーク自動生成アルゴリズム　　　　　　　　　　　　　　　
  大野 愉展; 原田 智広; 三浦 幸也
  First page：270, Last page：277, 2024
  Japanese, Symposium
  共同研究・競争的資金等ID：47716797
• Estimation of Information on the Pedestrian Traffic Using Crowd Simulation　　　　　　　　　　　　　　　
  Yuki Tanigaki, Shusuke Shigenaka, Shunki Takami, Masaki Onishi, Naoki Hamada, Tomohiro Harada
  Transaction of the Japanese Society for Evolutionary Computation, Volume：14, Number：1, First page：18, Last page：28, Dec. 2023, [Reviewed], [Invited], [Last]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.14.18
  DOI ID：10.11394/tjpnsec.14.18
• Report on Open Space Discussion 2022　　　　　　　　　　　　　　　
  Masaya Nakata; Takeshi Uchitane; Junichi Kushida; Shoichiro Tanaka; Yuki Tanigaki; Kei Nishihara; Tomohiro Harada; Yusuke Nojima
  Transaction of the Japanese Society for Evolutionary Computation, Volume：14, Number：1, First page：12, Last page：17, Dec. 2023, [Reviewed], [Invited]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.14.12
  DOI ID：10.11394/tjpnsec.14.12
• Emergence of Cooperative Automated Driving Control at Roundabouts Using Deep Reinforcement Learning　　　　　　　　　　　　　　　
  Reo Nakaya; Tomohiro Harada; Yukiya Miura; Kiyohiko Hattori; Johei Matsuoka
  2023 62nd Annual Conference of the Society of Instrument and Control Engineers (SICE), Volume：483, First page：97, Last page：102, Sep. 2023, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.23919/sice59929.2023.10354212
  DOI ID：10.23919/sice59929.2023.10354212, DBLP ID：conf/sice/NakayaHMHM23
• Hybrid Rocket Engine Design Using Pairwise Ranking Surrogate-assisted Differential Evolution　　　　　　　　　　　　　　　
  Hitomi Kano; Tomohiro Harada; Yukiya Miura; Masahiro Kanazaki
  Proceedings of the Companion Conference on Genetic and Evolutionary Computation, First page：1956, Last page：1962, Jul. 2023, [Reviewed], [Corresponding]
  ACM, English, International conference proceedings
  DOI：https://doi.org/10.1145/3583133.3596379
  DOI ID：10.1145/3583133.3596379, DBLP ID：conf/gecco/KanoHMK23
• A pairwise ranking estimation model for surrogate-assisted evolutionary algorithms
  Tomohiro Harada
  Complex & Intelligent Systems, Jun. 2023, [Reviewed], [Lead, Last, Corresponding]
  Abstract
  
  Surrogate-assisted evolutionary algorithms (SAEAs) have attracted considerable attention for reducing the computation time required by an EA on computationally expensive optimization problems. In such algorithms, a surrogate model estimates the solution evaluation with a low computing cost and is used to obtain promising solutions to which the accurate evaluation with an expensive computation cost is then applied. This study proposes a novel pairwise ranking surrogate model called the Extreme Learning-machine-based DirectRanker (ELDR). ELDR integrates two machine learning models: extreme learning machine (ELM) and DirectRanker (DR). ELM is a single-layer neural network capable of fast learning, whereas DR uses pairwise learning to rank using a neural network developed mainly for information retrieval. To investigate the effectiveness of the proposed surrogate model, this study first examined the estimation accuracy of ELDR. Subsequently, ELDR was incorporated into a state-of-the-art SAEA and compared with existing SAEAs on well-known real-valued optimization benchmark problems. The experimental results revealed that ELDR has a high estimation accuracy even on high-dimensional problems with a small amount of training data. In addition, the SAEA using ELDR exhibited a high search performance compared with other existing SAEAs, especially on high-dimensional problems.
  Springer Science and Business Media LLC, English, Scientific journal
  DOI：https://doi.org/10.1007/s40747-023-01113-4
  DOI ID：10.1007/s40747-023-01113-4, ISSN：2199-4536, eISSN：2198-6053
• Investigating the influence of survival selection and fitness estimation method in genotype-based surrogate-assisted genetic programming.　　　　　　　　　　　　　　　
  Tomohiro Harada; Sohei Kino; Ruck Thawonmas
  Artificial Life and Robotics, Volume：28, Number：1, First page：181, Last page：191, Feb. 2023, [Reviewed], [Lead, Corresponding]
  English, Scientific journal
  DOI：https://doi.org/10.1007/s10015-022-00821-3
  DOI ID：10.1007/s10015-022-00821-3, DBLP ID：journals/alr/HaradaKT23
• Behavior analysis of emergent rule discovery for cooperative automated driving using deep reinforcement learning.　　　　　　　　　　　　　　　
  Tomohiro Harada; Johei Matsuoka; Kiyohiko Hattori
  Artificial Life and Robotics, Volume：28, Number：1, First page：31, Last page：42, Feb. 2023, [Reviewed], [Lead, Corresponding]
  English, Scientific journal
  DOI：https://doi.org/10.1007/s10015-022-00839-7
  DOI ID：10.1007/s10015-022-00839-7, DBLP ID：journals/alr/HaradaMH23
• A frequency-based parent selection for reducing the effect of evaluation time bias in asynchronous parallel multi-objective evolutionary algorithms　　　　　　　　　　　　　　　
  Tomohiro Harada
  Natural Computing, Volume：abs/2107.12053, Dec. 2022, [Reviewed], [Lead, Last, Corresponding]
  Springer Science and Business Media LLC, English, Scientific journal
  DOI：https://doi.org/10.1007/s11047-022-09940-z
  DOI ID：10.1007/s11047-022-09940-z, ISSN：1567-7818, eISSN：1572-9796, DBLP ID：journals/corr/abs-2107-12053
• Differential Evolution Using Surrogate Model Based on Pairwise Ranking Estimation for Constrained Optimization Problems　　　　　　　　　　　　　　　
  Hitomi Kano; Tomohiro Harada; Yukiya Miura
  2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS), First page：1, Last page：6, Nov. 2022, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/scisisis55246.2022.10001982
  DOI ID：10.1109/scisisis55246.2022.10001982, DBLP ID：conf/scisisis/KanoHM22
• Improving Data Sampling Efficiency of Sensitivity Analysis Based on Bilevel Multi-objective Evolutionary Algorithm　　　　　　　　　　　　　　　
  Takuya Hakoishi; Tomohiro Harada; Yukiya Miura
  2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS), First page：1, Last page：6, Nov. 2022, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/scisisis55246.2022.10001967
  DOI ID：10.1109/scisisis55246.2022.10001967, DBLP ID：conf/scisisis/HakoishiHM22
• Design of Subsidy Payment Policies with Social Simulation　　　　　　　　　　　　　　　
  Yusuke Goto, Hiroyuki Morita, Yasuyuki Shirai, Hisashi Ichikawa, Naoki Hamada, Tomohiro Harada
  Transaction of the Japanese Society for Evolutionary Computation, Volume：13, Number：1, First page：23, Last page：39, Sep. 2022, [Reviewed], [Last]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.13.23
  DOI ID：10.11394/tjpnsec.13.23
• A fresh approach to evaluate performance in distributed parallel genetic algorithms　　　　　　　　　　　　　　　
  Tomohiro Harada; Enrique Alba; Gabriel Luque
  Applied Soft Computing, Volume：119, First page：108540, Last page：108540, Apr. 2022, [Reviewed], [Lead, Corresponding]
  Elsevier BV, English, Scientific journal
  DOI：https://doi.org/10.1016/j.asoc.2022.108540
  DOI ID：10.1016/j.asoc.2022.108540, ISSN：1568-4946, ORCID：107583612, 共同研究・競争的資金等ID：27301248
• Parallel Genetic Algorithms
  Tomohiro Harada; Enrique Alba
  ACM Computing Surveys, Volume：53, Number：4, First page：1, Last page：39, Jul. 2021, [Reviewed], [Lead, Corresponding]
  Association for Computing Machinery (ACM), Scientific journal
  DOI：https://doi.org/10.1145/3400031
  DOI ID：10.1145/3400031, ISSN：0360-0300, eISSN：1557-7341, ORCID：105654189, SCOPUS ID：85092186001
• Adaptation of Search Generations in Extreme Learning Assisted MOEA/D Based on Estimation Accuracy of Surrogate Model　　　　　　　　　　　　　　　
  Koki Tsujino; Tomohiro Harada; Ruck Thawonmas
  2021 IEEE Congress on Evolutionary Computation (CEC), Volume：11, First page：1519, Last page：1526, Jun. 2021, [Reviewed], [Corresponding]
  In the last decade, multi-objective evolutionary algorithms (MOEAs) have been utilized for many real-world applications. However, it takes a great deal of computation time for the majority of real-world problems to obtain the optimal solutions due to the expensive fitness evaluation cost. In order to reduce the computation time for optimization, surrogate-assisted MOEAs have been studied. Our previous study analyzed ELMOEA/D, one of the surrogate-assisted MOEA combining MOEA/D with an extreme learning machine (ELM), from the relation between search performance and search generations. Our previous analysis revealed that the search generations on the surrogate space must be determined to make the accuracy of the surrogate model low. For this fact, this paper proposes the automatic adjustment methods for the search generations of ELMOEA/D. We conduct experiments with several well-known multi-objective benchmark problems and compare the proposed methods with the conventional ELMOEA/D with the fixed number of generations. The experimental results reveal that the proposed methods achieve a more stable search performance than ELMOEA/D with the fixed number of generations regardless of the target problems.
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/cec45853.2021.9504819
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85124630645&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85124630645&origin=inward
  DOI ID：10.1109/cec45853.2021.9504819, DBLP ID：conf/cec/TsujinoHT21, SCOPUS ID：85124630645
• Parallel differential evolution applied to interleaving generation with precedence evaluation of tentative solutions　　　　　　　　　　　　　　　
  Hayato Noguchi; Tomohiro Harada; Ruck Thawonmas
  Proceedings of the Genetic and Evolutionary Computation Conference, First page：706, Last page：713, Jun. 2021, [Reviewed], [Corresponding]
  This paper proposes a method to improve the CPU utilization of parallel differential evolution (PDE) by incorporating the interleaving generation mechanism. Previous research proposed the interleaving generation evolutionary algorithm (IGEA) and its improved variants (iIGEA). IGEA reduces the computation time by generating new offspring, which parents have been determined even when all individuals have not evaluated. However, the previous research only used a simple EA method, which is not suitable for practical use. For this issue, this paper explores the applicability of IGEA and iIGEA to practical EA methods. In particular, we choose differential evolution (DE), which is widely used in real-world applications, and propose IGDE and its improved variant, iIGDE. We conduct experiments to investigate the effectiveness of IGDE with several features of the evaluation time on a simulated parallel computing environment. The experimental results reveal that the IGDE variants have higher CPU utilization than a simple PDE and reduce the computation time required for optimization. Besides, iIGDE outperforms the original IGDE for all features of the evaluation time.
  ACM, English, International conference proceedings
  DOI：https://doi.org/10.1145/3449639.3459337
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85110232828&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85110232828&origin=inward
  DOI ID：10.1145/3449639.3459337, DBLP ID：conf/gecco/NoguchiHT21, SCOPUS ID：85110232828
• Random Number Generation Problems based on Cognitive Biases for In-Game Events　　　　　　　　　　　　　　　
  Naoki Hamada; Suguru Oho; Yuki Tanigaki; Tomohiro Harada; Yusuke Nojima
  Transaction of the Japanese Society for Evolutionary Computation, Volume：12, Number：3, First page：112, Last page：124, 2021, [Reviewed]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.12.112
  DOI ID：10.11394/tjpnsec.12.112
• Improving CPU utilization of interleaving generation parallel evolutionary algorithm with precedence evaluation of tentative solutions and their suspension
  Hayato Noguchi; Akari Sonoda; Tomohiro Harada; Ruck Thawonmas
  SICE Journal of Control, Measurement, and System Integration, Volume：14, Number：1, First page：242, Last page：256, Jan. 2021, [Reviewed], [Corresponding]
  Informa UK Limited, English, Scientific journal
  DOI：https://doi.org/10.1080/18824889.2021.1972386
  DOI ID：10.1080/18824889.2021.1972386, ISSN：1882-4889, eISSN：1884-9970, ORCID：99848052
• A Study on Efficient Asynchronous Parallel Multi-objective Evolutionary Algorithm with Waiting Time Limitation
  Tomohiro Harada
  Lecture Notes in Computer Science, First page：121, Last page：132, Nov. 2020, [Reviewed], [Lead, Last, Corresponding]
  Springer International Publishing, English, In book
  DOI：https://doi.org/10.1007/978-3-030-63000-3_10
  DOI ID：10.1007/978-3-030-63000-3_10, ISSN：0302-9743, eISSN：1611-3349, ORCID：95421880, SCOPUS ID：85097654428
• Analysis of Relation between Prediction Accuracy of Surrogate Model and Search Performance on Extreme Learning Machine Assisted MOEA/D　　　　　　　　　　　　　　　
  Koki Tsujino; Tomohiro Harada; Ruck Thawonmas
  2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020, First page：820, Last page：825, Sep. 2020, [Reviewed], [Corresponding]
  In recent years, evolutionary algorithms have been used for many real-world problems, but it takes enormous computation time to obtain the optimal solution due to its high calculation cost. Multi-objective evolutionary algorithms using surrogate models have been studied to reduce the computation time for the optimization. ELMOEA/D is one of the surrogate-assisted multi-objective evolutionary algorithms. ELMOEA/D combines MOEA/D with an extreme learning machine (ELM). This paper analyzes the relation between the estimation accuracy of the surrogate model and the search performance of ELMOEA/D. We experiment on several well-known multi-objective benchmark problems and compare the different number of generations. The experimental results reveal that the estimation accuracy and the search performance decrease as the number of generations increase.
  English, International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096352943&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85096352943&origin=inward
  SCOPUS ID：85096352943
• Proposal of Surrogate Model for Genetic Programming Based on Program Structure Similarity　　　　　　　　　　　　　　　
  Sohei Kino; Tomohiro Harada; Ruck Thawonmas
  2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020, First page：808, Last page：813, Sep. 2020, [Reviewed], [Corresponding]
  This paper proposes a novel surrogate model for genetic programming that estimates the fitness of each individual by using the tree structure similarity. In particular, the fitness of each individual is estimated with the nearest neighbor method by comparing each individual with the evaluated population. We conduct an experiment to investigate the effectiveness of the proposed method. In the experiment, we compare genetic programming with and without the proposed surrogate model on the symbolic regression problem. We assess the convergence speed and the discovery ratio of the optimum program. The experimental result reveals that the proposed method improves the convergence speed of genetic programming while maintaining the discovery rate of the optimum program.
  English, International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096355291&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85096355291&origin=inward
  SCOPUS ID：85096355291
• Interleaving Generation Evolutionary Algorithm with Precedence Evaluation of Tentative Offspring　　　　　　　　　　　　　　　
  Hayato Noguchi; Akari Sonoda; Tomohiro Harada; Ruck Thawonmas
  2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2020, First page：832, Last page：837, Sep. 2020, [Reviewed], [Corresponding]
  This paper proposes the method to improve the CPU utilization by using precedence evaluation of tentative offspring for the previous method. The previous research proposed the Interleaving Generation Evolutionary Algorithm (IGEA) that generates individuals which parents are evaluated before the evaluation of all individuals completed. IGEA can reduce the execution time for the optimization with EA. We compare the proposed method with the original IGEA and investigate the effectiveness of the proposed method. The experimental results show that the proposed method has higher CPU utilization than the original IGEA.
  English, International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096357354&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85096357354&origin=inward
  SCOPUS ID：85096357354
• Oil Leak Detection with Machine Learning and Topological Data Analysis　　　　　　　　　　　　　　　
  Syuuya Ohtomo; Tomohiro Harada; Ruck Thawonmas; Takuo Ito
  Volume：61, Number：8, First page：1294, Last page：1305, Aug. 2020, [Reviewed], [Corresponding]
  Japanese, Scientific journal
• Proposal of Multimodal Program optimization Benchmark and Its Application to Multimodal Genetic Programming　　　　　　　　　　　　　　　
  Tomohiro Harada; Kei Murano; Ruck Thawonmas
  2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings, Jul. 2020, [Reviewed], [Corresponding]
  © 2020 IEEE. Multimodal program optimizations (MMPOs) have been studied in recent years. MMPOs aims at obtaining multiple optimal programs with different structures simultaneously. This paper proposes novel MMPO benchmark problems to evaluate the performance of the multimodal program search algorithms. In particular, we propose five MMPOs, which have different characteristics, the similarity between optimal programs, the complexity of optimal programs, and the number of local optimal programs. We apply multimodal genetic programming (MMGP) proposed in our previous work to the proposed MMPOs to verify their difficulty and effectiveness, and evaluate the performance of MMGP. The experimental results reveal that the proposed MMPOs are difficult and complex to obtain the global and local optimal programs simultaneously as compared to the conventional benchmark. In addition, the experimental results clarify mechanisms to improve the performance of MMGP.
  English, International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85092068217&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85092068217&origin=inward
• Comparison of synchronous and asynchronous parallelization of extreme surrogate-assisted multi-objective evolutionary algorithm　　　　　　　　　　　　　　　
  Tomohiro Harada; Misaki Kaidan; Ruck Thawonmas
  Natural Computing, Volume：21, Number：2, First page：187, Last page：217, 2020, [Reviewed], [Lead, Corresponding]
  © 2020, The Author(s). This paper investigates the integration of a surrogate-assisted multi-objective evolutionary algorithm (MOEA) and a parallel computation scheme to reduce the computing time until obtaining the optimal solutions in evolutionary algorithms (EAs). A surrogate-assisted MOEA solves multi-objective optimization problems while estimating the evaluation of solutions with a surrogate function. A surrogate function is produced by a machine learning model. This paper uses an extreme learning surrogate-assisted MOEA/D (ELMOEA/D), which utilizes one of the well-known MOEA algorithms, MOEA/D, and a machine learning technique, extreme learning machine (ELM). A parallelization of MOEA, on the other hand, evaluates solutions in parallel on multiple computing nodes to accelerate the optimization process. We consider a synchronous and an asynchronous parallel MOEA as a master-slave parallelization scheme for ELMOEA/D. We carry out an experiment with multi-objective optimization problems to compare the synchronous parallel ELMOEA/D with the asynchronous parallel ELMOEA/D. In the experiment, we simulate two settings of the evaluation time of solutions. One determines the evaluation time of solutions by the normal distribution with different variances. On the other hand, another evaluation time correlates to the objective function value. We compare the quality of solutions obtained by the parallel ELMOEA/D variants within a particular computing time. The experimental results show that the parallelization of ELMOEA/D significantly reduces the computational time. In addition, the integration of ELMOEA/D with the asynchronous parallelization scheme obtains higher quality of solutions quicker than the synchronous parallel ELMOEA/D.
  Springer Science and Business Media {LLC}, English, Scientific journal
  DOI：https://doi.org/10.1007/s11047-020-09806-2
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091183733&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85091183733&origin=inward
  DOI ID：10.1007/s11047-020-09806-2, ISSN：1567-7818, eISSN：1572-9796, ORCID：80758844, SCOPUS ID：85091183733, 共同研究・競争的資金等ID：27301248
• Using Graph Convolution Network for Predicting Performance of Automatically Generated Convolution Neural Networks
  Enzhi Zhang; Tomohiro Harada; Ruck Thawonmas
  2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), Volume：8, First page：1, Last page：8, Dec. 2019, [Reviewed], [Corresponding]
  IEEE, English, International conference proceedings
  DOI：https://doi.org/10.1109/csde48274.2019.9162354
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85094680656&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85094680656&origin=inward
  DOI ID：10.1109/csde48274.2019.9162354, SCOPUS ID：85094680656
• Improving Brain Memory through Gaming Using Hand Clenching and Spreading
  Yunshi Liu; Febri Abdullah; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  Motion, Interaction and Games, First page：1, Last page：3, Oct. 2019, [Reviewed]
  ACM, English, International conference proceedings
  DOI：https://doi.org/10.1145/3359566.3364689
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074827554&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85074827554&origin=inward
  DOI ID：10.1145/3359566.3364689, SCOPUS ID：85074827554
• Player dominance adjustment motion gaming AI for health promotion　　　　　　　　　　　　　　　
  Junjie Xu; Pujana Paliyawan; Yiming Zhang; Ruck Thawonmas; Tomohiro Harada
  Proceedings - MIG 2019: ACM Conference on Motion, Interaction, and Games, Oct. 2019
  This paper presents an opponent fighting game AI for promoting balancedness in use of body segments of the player during full-body motion gaming. The proposed AI, named PDAHP-AI, is based on Monte Carlo tree-search and employs a recently purposed concept called Player Dominance Adjustment, where the AI determines its actions based on the player’s inputs so as to adjust the player’s dominant power. The basic idea is to let the player dominate the game when they perform healthy movement and on the contrary to have the AI take a strong action against the player when she or he performs unhealthy movement. The AI outperforms an existing dynamic difficulty adjustment AI designed for the same propose.
  International conference proceedings
  DOI：https://doi.org/10.1145/3359566.3364690
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85074848768&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85074848768&origin=inward
  DOI ID：10.1145/3359566.3364690, SCOPUS ID：85074848768
• Player dominance adjustment: Promoting self-efficacy and experience of game players by adjusting dominant power　　　　　　　　　　　　　　　
  Junjie Xu; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, First page：487, Last page：488, Oct. 2019
  This paper presents an idea of promoting game-related self-efficacy and user experience of game players by adjusting their dominant power. The assumption is that game players will gain higher self-efficacy and better gameplay experience when game situations go in the way they expect. To evaluate this assumption, we conduct a pilot study using a famous social deduction game called Werewolf by letting human players play this game, one player at a time over the Internet. In the pilot-study setting, each participant thinks that he/she plays with other six players, but all the other players are in fact controlled by the experimenter. Game situations are manipulated to create two cases of gameplay: (1) a case in which most of the participant's actions impact gameplay (player-dominance games), and (2) a case in which almost none of the participant's actions impact gameplay (non-player-dominance games). The findings based on evaluation using General Self-Efficacy Scale and Game User Experience Satisfaction Scale are that player-dominance games lead to higher self-efficacy, and there is a strong linear relationship between self-efficacy and enjoyment.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE46687.2019.9015408
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081955324&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85081955324&origin=inward
  DOI ID：10.1109/GCCE46687.2019.9015408, SCOPUS ID：85081955324
• Enhance physical and mental well-being of game players in an endless running game　　　　　　　　　　　　　　　
  Sunee Sae-Lao; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, First page：945, Last page：946, Oct. 2019
  This paper presents new features added to Runner, an open-source 2D-platform running game designed for games for health research. This game can be played by using body motion through a Kinect device, and the original version of the game is focused on physical health promotion and facial expression by video camera. We present a new mode that aims at enhancing mental well-being through a smile detection mechanism. An integration between motion detection and facial expression detection is presented.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE46687.2019.9015570
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081959815&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85081959815&origin=inward
  DOI ID：10.1109/GCCE46687.2019.9015570, SCOPUS ID：85081959815
• An analysis of highlight-oriented ai using fighting-game experience　　　　　　　　　　　　　　　
  Ryota Ishii; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, First page：551, Last page：552, Oct. 2019
  In this paper, we verify whether the spectator's game experience affects the enjoyment of watching gameplay by AI. In recent years, watching gameplay has become one of the main contents of games. Therefore, research has been conducted to automatically generate gameplay for spectators. In this paper, we analyze the AI gameplay proposed in CoG 2019 using the spectators' game experience. The analysis shows that the gameplay by AI is fun regardless of the amount of experience in the fighting game.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE46687.2019.9015372
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081975079&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85081975079&origin=inward
  DOI ID：10.1109/GCCE46687.2019.9015372, SCOPUS ID：85081975079
• Towards an angry-birds-like game system for promoting mental well-being of players using art-therapy-embedded procedural content generation　　　　　　　　　　　　　　　
  Zhou Fang; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019, First page：947, Last page：948, Oct. 2019
  This paper presents an integration of a game system and the art therapy concept for promoting the mental well-being of video game players. In the proposed game system, the player plays an Angry-Birds-like game in which levels in the game are generated based on images they draw. Upon finishing a game level, the player also receives positive feedback (praising words) toward their drawing and the generated level from an Art Therapy AI. The proposed system is composed of three major parts: (1) a drawing recognizer that identifies what object is drawn by the player (Sketcher), (2) a level generator that converts the drawing image into a pixel image, then a set of blocks representing a game level (PCG AI), and (3) the Art Therapy AI that encourages the player and improves their emotion. This paper describes an overview of the system and explains how its major components function.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE46687.2019.9015247
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081978406&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85081978406&origin=inward
  DOI ID：10.1109/GCCE46687.2019.9015247, SCOPUS ID：85081978406
• Promoting Emotional Well-Being with Angry-Birds-like Gameplay on Pixel Image Levels　　　　　　　　　　　　　　　
  Jingdi Xu; Yuuki Okido; Sunee Sae-Lao; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE 7th International Conference on Serious Games and Applications for Health, SeGAH 2019, Aug. 2019
  This paper describes the use of 'Real Pixel Image Level Generator (RPILG)' along with a design of game control, called 'enhancing play with smiling' to promote the players' emotion. Our study is conducted on Science Birds, an Angry-Birds-like game. RPILG is a procedural content generation method that generates game levels with the appearance of a pixel image of things, such as a pumpkin. We apply RPILG in Science Birds. A facial expression tool is used to recognize smiles in the player. And in our design, the black bird, a kind of shooting object in the game having the power to explode blocks, is modified such that its explosion power can be enhanced according to the degree of smiling. The idea behind this game design is to encourage smiling. An experiment is conducted with fourteen participants where two modes of gameplay 'smiling for enhancing the birds' and 'baseline play' are compared. An online survey using Positive and Negative Affect Schedule is used to evaluate the players' emotion after they have experienced both modes. Our experimental results provide an evidence that the former mode leads to statistically significantly higher positive affect and lower negative affect.
  International conference proceedings
  DOI：https://doi.org/10.1109/SeGAH.2019.8882454
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073103392&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85073103392&origin=inward
  DOI ID：10.1109/SeGAH.2019.8882454, SCOPUS ID：85073103392
• Motion gaming AI using time series forecasting and dynamic difficulty adjustment　　　　　　　　　　　　　　　
  Takahiro Kusano; Yunshi Liu; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2019-August, Aug. 2019
  This paper proposes a motion gaming AI that encourages players to use their body parts in a well-balanced manner while promoting their player experience. The proposed AI is an enhanced version of our previous AI in two aspects. First, it uses time series forecasting to more precisely predict what actions the player will perform with respect to its candidate actions, based on which the amount of movement to be produced on each body part of the player against each of such candidates is derived; as in our previous work. the AI selects its action from those candidates with a goal of making the player's movement of their body parts on both sides equal. Second, this AI employs Monte-Carlo tree search that finds candidate actions according to dynamic difficulty adjustment. Our results show that the proposed game AI outperforms our previous AI in terms of the player's body-movement balancedness, enjoyment, engrossment, and personal gratification.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2019.8847991
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073111720&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85073111720&origin=inward
  DOI ID：10.1109/CIG.2019.8847991, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85073111720
• A fighting game AI using highlight cues for generation of entertaining gameplay　　　　　　　　　　　　　　　
  Ryota Ishii; Suguru Ito; Ruck Thawonmas; Tomohiro Harada
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2019-August, Aug. 2019
  In this paper, we propose a fighting game AI that selects its actions from the perspective of highlight generation using Monte-Carlo tree search (MCTS) with three highlight cues in the evaluation function. The proposed AI is targeted for being used to generate gameplay in live streaming platforms such as Twitch and YouTube where a large number of spectators watch gameplay to entertain themselves. Our results in a user study conducted using FightingICE, a fighting game platform used in an international game AI competition since 2013, show that gameplay generated by the proposed AI is more entertaining than that by a typical MCTS AI. Detailed analyses of gameplay from all the methods assessed in the user study are also given in the paper.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2019.8848069
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073120622&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85073120622&origin=inward
  DOI ID：10.1109/CIG.2019.8848069, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85073120622
• An angry birds level generator with rube goldberg machine mechanisms　　　　　　　　　　　　　　　
  Febri Abdullah; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada; Fitra A. Bachtiar
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2019-August, Aug. 2019
  This study proposes a method for generating Angry Birds-like game levels featuring a domino effect generated based on Rube Goldberg Machine (RGM) mechanisms, which allow them to be completed by one shot of a bird. The proposed method generates a level by selecting predefined segments consisting of several objects arranged in a way that creates a domino effect among them. To increase the variability of generated levels, the proposed method procedurally generates a varying structure on the top of certain blocks in a predefined segment. Our results show that the proposed RGM generator is comparable to two existing generators, including the winner of the 2018 AIBIRDS Level Generation Competition, in terms of stability while it outperforms both baseline generators with respect to running time and an expressivity metric called "dynamic" which is introduced in this work to measure the time period where moving objects, including a shooting bird, reside in a given level. In addition, from the perspective on the destructive power of a shot, the proposed generator can generate levels featuring a successful domino effect with a high probability, in particular for levels with three to four segments.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2019.8847996
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073123157&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85073123157&origin=inward
  DOI ID：10.1109/CIG.2019.8847996, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85073123157
• Multimodal genetic programming using program similarity measurement and its application to wall-following problem　　　　　　　　　　　　　　　
  Shubu Yoshida; Tomohiro Harada; Ruck Thawonmas
  GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, First page：356, Last page：357, Jul. 2019
  In this paper, we examine the effectiveness of multimodal genetic programming (MMGP) on the wall-following problem, which is a well-known benchmark problem of genetic programming (GP). MMGP aims to obtain multiple local optimal programs, including global optimal programs, that is, programs that achieve the same goal with different program structures. In this paper, we apply MMGP to the wall-following problem. The purpose of the wall-following problem is to find a program to control a robot having twelve distance sensors and four movements to follow irregular walls. We expect that there are several local optimal programs in the wall-following problem, which use different combinations of sensors. An experiment is conducted to investigate whether MMGP can get local optimal programs simultaneously for the wall-following problem. This experiment compares MMGP with a simple GP. The experimental results reveal that MMGP can achieve higher acquisition ratio of local optimal programs than the simple GP.
  International conference proceedings
  DOI：https://doi.org/10.1145/3319619.3322063
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85070623336&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85070623336&origin=inward
  DOI ID：10.1145/3319619.3322063, SCOPUS ID：85070623336
• Improving rolling horizon evolutionary algorithm in a fighting game　　　　　　　　　　　　　　　
  Hayato Noguchi; Ryota Ishii; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2019 NICOGRAPH International, NicoInt 2019, First page：118, Jul. 2019
  In this paper, we examine the performance of a game AI using Rolling Horizon Evolutionary Algorithm (RHEA) for a fighting game. We propose two methods for improving RHEA. Our experimental results show that the proposed AI is superior to an AI using standard RHEA.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOInt.2019.00032
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078819628&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85078819628&origin=inward
  DOI ID：10.1109/NICOInt.2019.00032, SCOPUS ID：85078819628
• A visual analysis of gameplay in a fighting game　　　　　　　　　　　　　　　
  Suguru Ito; Suguru Ito; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2019 NICOGRAPH International, NicoInt 2019, First page：117, Jul. 2019
  In this paper, we perform a visual analysis of gameplay in a fighting game. In recent years, game streaming is actively performed on platforms typified by Twitch. In order to cope with an increase in the number of users watching such streaming, a method for generating gameplay by AI and providing it to spectators has been recently proposed by our group. However, it is necessary to verify beforehand whether the generated gameplay is appropriate for streaming. Therefore, in this paper, we locate such an issue and describe our improvement plan.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOInt.2019.00031
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078819661&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85078819661&origin=inward
  DOI ID：10.1109/NICOInt.2019.00031, SCOPUS ID：85078819661
• Self-play for training general fighting game AI　　　　　　　　　　　　　　　
  Yoshina Takano; Hideyasu Inoue; Ruck Thawonmas; Tomohiro Harada
  Proceedings - 2019 NICOGRAPH International, NicoInt 2019, First page：120, Jul. 2019
  In this paper, we train a general fighting game AI from self-play games to outperform an unseen opponent AI. It has been reported that an AI using Deep Q Network (DQN) can outperform the training partner. However, according to our experience, the DQN AI is not always superior to a new opponent, unseen before. By learning from self-play, we overcome this drawback while maintaining the DQN AI's strong points. Our experimental results show that it is more effective to use a variety of AIs with different behaviors as training partners.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOInt.2019.00034
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078855223&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85078855223&origin=inward
  DOI ID：10.1109/NICOInt.2019.00034, SCOPUS ID：85078855223
• Verification of applying curiosity-driven to fighting game AI　　　　　　　　　　　　　　　
  Hideyasu Inoue; Yoshina Takano; Ruck Thawonmas; Tomohiro Harada
  Proceedings - 2019 NICOGRAPH International, NicoInt 2019, First page：119, Jul. 2019
  In this paper, we apply a curiosity-driven intrinsic reward to reinforcement learning (RL) in a fighting game and verify its effectiveness. An actor-critic model is used for RL. Our experimental results show that the proposed AI has a better learning ability than an AI using a standard actor-critic model.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOInt.2019.00033
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078867151&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85078867151&origin=inward
  DOI ID：10.1109/NICOInt.2019.00033, SCOPUS ID：85078867151
• Promoting Emotions with Angry Birds-like Gameplay on Rube Goldberg Machine Levels　　　　　　　　　　　　　　　
  Febri Abdullah; Changeun Yang; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada; Fitra A. Bachtiar
  2019 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2019, First page：149, Last page：150, Jun. 2019
  This paper proposes a method for generating Angry Birds-like game levels, and their gameplays, that promote spectator's emotions. Each of such levels features a domino effect generated based on Rube Goldberg Machine (RGM) mechanisms, allowing it to be completed by one perfect shot of a bird. We evaluate the effects on spectator's emotions by comparing two sets of gameplay videos; one with only perfect shots and the other with only imperfact shots (i.e., gameplays that were not successfully completed by one shot). We conducted an online survey using Positive and Negative Affect Schedule (PANAS) to evaluate the spectator's emotions before and after watching a video of interest. Our results show that perfect-shot videos lead to higher positive affect and lower negative affect of the spectator in the same series of generated RGM levels. In addition, the perfect-shot video has a stronger evidence in decreasing the negative affect of the spectator than the imperfect one.
  International conference proceedings
  DOI：https://doi.org/10.1109/ICCE-Asia46551.2019.8941596
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073097917&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85073097917&origin=inward
  DOI ID：10.1109/ICCE-Asia46551.2019.8941596, SCOPUS ID：85073097917
• Using GWAP to Generate Informative Descriptions for Artwork Images on a Live Streaming Platform　　　　　　　　　　　　　　　
  Ngoc Cuong Nguyen; Zhenao Wei; Pujana Paliyawan; Hai V. Pham; Ruck Thawonmas; Tomohiro Harada
  2019 IEEE International Conference on Consumer Electronics - Asia, ICCE-Asia 2019, First page：43, Last page：44, Jun. 2019
  This paper proposes a method for creating informative descriptive sentences for artwork images by using "Games With a Purpose," or GWAP on a live streaming platform. In existing studies, automatic annotation of images did not perform well, in particular, for artwork images such as Ukiyo-e. On the other hand, existing studies on GWAP, the concept of using games for human to address problems that computer cannot solve, demonstrated how games can exploit human intelligence in labeling images. With a huge number of audiences watching games live streaming on Twitch and other similar services nowadays, we propose a solution that makes chatting of audiences become an effective means for generating valuable descriptions for artwork images, Ukiyo-e images in this study, as well as promoting the interaction between the audiences and the game.
  International conference proceedings
  DOI：https://doi.org/10.1109/ICCE-Asia46551.2019.8941600
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078071010&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85078071010&origin=inward
  DOI ID：10.1109/ICCE-Asia46551.2019.8941600, SCOPUS ID：85078071010
• Analysis of semi-asynchronous multi-objective evolutionary algorithm with different asynchronies
  Tomohiro Harada; Keiki Takadama
  Soft Computing, Volume：24, Number：4, First page：2917, Last page：2939, May 2019, [Reviewed], [Lead, Corresponding]
  Springer Science and Business Media LLC, English, Scientific journal
  DOI：https://doi.org/10.1007/s00500-019-04071-7
  DOI ID：10.1007/s00500-019-04071-7, ISSN：1432-7643, eISSN：1433-7479, ORCID：60076152, SCOPUS ID：85066099031
• TGIF!: Selecting the most healing TNT by optical flow　　　　　　　　　　　　　　　
  AAAI 2019 Spring Symposium on "Interpretable AI for Well-Being: Understanding Cognitive Bias and Social Embeddedness, Mar. 2019
• 月面着陸最適候補の多目的選定問題におけるNSGA-IIとVNSを用いる最適化手法の提案　　　　　　　　　　　　　　　
  第15回進化計算学会研究会, Mar. 2019
• Utilizing Multiple Agents for Decision Making in a Fighting Game　　　　　　　　　　　　　　　
  Yoshina Takano; Suguru Ito; Tomohiro Harada; Ruck Thawonmas
  2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, First page：341, Last page：342, Dec. 2018
  In this paper, we propose a method for implementing a competent game AI using two expert agents that are separately trained for different purposes. Deep reinforcement learning (DRL) has been successfully applied to achieve human-level results for many types of games. However, DRL has not yet been successfully applied to fighting games in terms of performance. We, thus, examine if a competent fighting game AI can be implemented by DRL. The proposed method uses two expert agents which are trained using separate Deep Q-Networks (DQNs) for a fighting game AI. For performance evaluation, we use FightingICE which has been used as a game platform in a game AI competition at a game-AI international conference since 2014. Our experimental results show that proposed AI is superior to an AI using a single DQN.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2018.8574675
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060270430&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85060270430&origin=inward
  DOI ID：10.1109/GCCE.2018.8574675, SCOPUS ID：85060270430
• Blow Up Depression with In-Game TNTs　　　　　　　　　　　　　　　
  Changeun Yang; Pujana Paliyawan; Tomohiro Harada; Ruck Thawonmas
  2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, First page：186, Last page：189, Dec. 2018
  This paper proposes a TNT-generation system in Science Birds, an Angry Birds clone, which is aimed to help spectators maintain healthy emotion. Interestingness-rating data on TNT explosions are collected from a number of participants. A regressor is then built from the collected data whose input consists of a set of features representing effects due to an explosion and output indicates the average interestingness. A user study is then conducted where participants are asked to answer a questionnaire measuring their positive and negative affect after watching each of the three gameplay videos - the explosions with the highest average interestingness, the explosions with the lowest average interestingness, the explosions with the highest interestingness predicted by the regressor - in counterbalanced order. Our results show that the first gameplay video statistically significantly increases the positive affect of the participants and that both first and third videos statistically significantly decrease the negative affect.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2018.8574626
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060274465&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85060274465&origin=inward
  DOI ID：10.1109/GCCE.2018.8574626, SCOPUS ID：85060274465
• An Angry Birds-like Game System for Promoting Players' Emotion　　　　　　　　　　　　　　　
  Jingdi Xu; Changeun Yang; Yuuki Okido; Pujana Paliyawan; Ruck Thawonmas; Tomohiro Harada
  2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, First page：811, Last page：812, Dec. 2018
  This paper presents a system aimed at encouraging players to smile when playing an Angry Birds-like game by generating levels whose designs look like pixel images and explicitly requiring the players to smile to see such levels. Our system consists of two major parts: level generator and game system. The level generator generates a level according to a given file that defines the level appearance of a pixel image. The game system includes emotion recognition and fog control; to encourage the player to smile, fog is first generated that covers the game screen, but when the player smiles it will gradually disappear. It is expected that the proposed system is useful in promoting the affect of its players, i.e., increasing the positive affect and decreasing the negative one.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2018.8574848
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060283233&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85060283233&origin=inward
  DOI ID：10.1109/GCCE.2018.8574848, SCOPUS ID：85060283233
• An Analysis of Fighting Game AIs Having a Persona　　　　　　　　　　　　　　　
  Ryota Ishii; Suguru Ito; Ruck Thawonmas; Tomohiro Harada
  2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, First page：124, Last page：125, Dec. 2018
  In this paper, we analyze AIs having a specific persona in a fighting game. A persona represents a play style in a given game. In recent years, gameplay video watching is booming entertainment media. Therefore, there has been an increasing number of studies on gameplay video watching including ours aimed at automatically generating gameplay directed toward spectators. In this paper, we focus on AIs, having a persona, that we recently proposed. The results of a conducted experiment using FightingICE, a fighting game platform used in a game AI competition at IEEE Conference on Computational Intelligence and Games since 2014, show a high accuracy in realization of each persona of interest.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2018.8574759
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060289719&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85060289719&origin=inward
  DOI ID：10.1109/GCCE.2018.8574759, SCOPUS ID：85060289719
• An Object Matrix Input Format for a Deep AI in Angry Birds and the Like　　　　　　　　　　　　　　　
  Yuntian Ma; Enzhi Zhang; Koki Tsujino; Tomohiro Harada; Ruck Thawonmas
  2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, First page：57, Last page：59, Dec. 2018
  This paper describes how to improve the performance of a deep-convolution-neural-network AI by a new input format called object matrix in the popular game Angry Birds and the like. This method makes the AI agent only focus on game objects which are necessary for playing the game. Experimental results are provided that show a statistically significant increase of the neural network's accuracy by this input format in predicting positions to drag the current bird.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2018.8574799
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85060293276&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85060293276&origin=inward
  DOI ID：10.1109/GCCE.2018.8574799, SCOPUS ID：85060293276
• 月着陸探査ミッションの最適着陸地点選定問題に対する分散型局所探索法の有効性の検証　　　　　　　　　　　　　　　
  進化計算シンポジウム2018, Dec. 2018
• A Study on Multimodal Genetic Programming Introducing Program Simplification　　　　　　　　　　　　　　　
  Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018 (SCIS&ISIS 2018), Dec. 2018
• A Study on Multimodal Genetic Programming Introducing Program Simplification　　　　　　　　　　　　　　　
  Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems in conjunction with Intelligent Systems Workshop 2018 (SCIS&ISIS 2018), Dec. 2018
• 睡眠時無呼吸症候群患者のための無拘束型リアルタイム睡眠段階推定法　　　　　　　　　　　　　　　
  ヘルスケア・医療情報通信技術研究会（MICT）, Nov. 2018
• Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors　　　　　　　　　　　　　　　
  Makoto Ishihara; Suguru Ito; Ryota Ishii; Tomohiro Harada; Ruck Thawonmas
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2018-August, Oct. 2018
  In this paper, we propose a Monte-Carlo Tree Search (MCTS) fighting game AI capable of dynamic difficulty adjustment while maintaining believable behaviors. This work targets beginner-level and intermediate-level players. In order to improve players' skill while at the same time entertaining them, AIs are needed that can evenly fight against their opponent beginner and intermediate players, and such AIs are called dynamic difficulty adjustment (DDA) AIs. In addition, in order not to impair the players' playing motivation due to the AI's unnatural actions such as intentionally taking damage with no resistance, DDA methods considering restraint of its unnatural actions are needed. In this paper, for an MCTS-based AI previously proposed by the authors' group, we introduce a new evaluation term on action believability, to the AIs evaluation function, that focuses on the amount of damage to the opponent. In addition, we introduce a parameter that dynamically changes its value according to the current game situation in order to balance this new term with the existing one, focusing on adjusting the AI's skill equal to that of the player, in the evaluation function. Our results from the conducted experiment using FightingICE, a fighting game platform used in a game AI competition at CIG since 2014, show that the proposed DDA-AI can dynamically adjust its strength to its opponent human players, especially intermediate players, while restraining its unnatural actions throughout the game.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2018.8490376
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056849994&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85056849994&origin=inward
  DOI ID：10.1109/CIG.2018.8490376, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85056849994
• Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas　　　　　　　　　　　　　　　
  Ryota Ishii; Suguru Ito; Makoto Ishihara; Tomohiro Harada; Ruck Thawonmas
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2018-August, Oct. 2018
  In this paper, we propose a method for implementing a game AI with a persona using Monte-Carlo Tree Search (MCTS). Video games are now a powerful entertainment media not just for players but spectators as well. Since each spectator has personal preferences, customized spectator-specific gameplay is arguably a promising option to increase the entertainment value of video games streaming. In this paper, we focus on personas, which represent playstyles in the game, in particular fighting games. In order to create an AI player (character) with a given persona, we use a recently developed variant of MCTS called Puppet-Master MCTS, which controls all characters in the game, and introduce a new evaluation function, which makes each character take their actions according to the given persona, and roulette selection-based simulation to this MCTS. The results of a conducted experiment using FightingICE, a fighting game platform used in a game AI competition at CIG since 2014, show that the proposed method can make both characters successfully behave according to given personas, which were identified by participants - spectators - in the experiment.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2018.8490367
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056887056&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85056887056&origin=inward
  DOI ID：10.1109/CIG.2018.8490367, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85056887056
• Applying Hybrid Reward Architecture to a Fighting Game AI　　　　　　　　　　　　　　　
  Yoshina Takano; Wenwen Ouyang; Suguru Ito; Tomohiro Harada; Ruck Thawonmas
  IEEE Conference on Computatonal Intelligence and Games, CIG, Volume：2018-August, Oct. 2018
  In this paper, we propose a method for implementing a competent fighting game AI using Hybrid Reward Architecture (HRA). In 2017, an AI using HRA developed by Seijen et al. achieved a perfect score of 999,990 in Ms. Pac-Man. HRA decomposes a reward function into multiple components and learns a separate value function for each component in the reward function. Due to reward decomposition, an optimal value function can be learned in the domain of Ms. Pac-Man. However, the number of actions in Ms. Pac-Man is only limited to four (Up, Down, Left, and Right), and till now whether HRA is also effective in other games with a larger number of actions is unclear. In this paper, we apply HRA and verify its effectiveness in a fighting game. For performance evaluation, we use FightingICE that has 40 actions and has been used as the game platform in the Fighting Game AI Competition at CIG since 2014. Our experimental results show that the proposed HRA AI, a new sample AI for the competition, is superior to non-HRA deep learning AIs and is competitive against other entries of the 2017 competition.
  International conference proceedings
  DOI：https://doi.org/10.1109/CIG.2018.8490437
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056906410&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85056906410&origin=inward
  DOI ID：10.1109/CIG.2018.8490437, ISSN：2325-4270, eISSN：2325-4289, SCOPUS ID：85056906410
• An Object Matrix Input Format for a Deep AI in Angry Birds and the like　　　　　　　　　　　　　　　
  2018 IEEE 7th Global Conference on Consumer Electronics (GCCE 2018), Oct. 2018
• 複数車種の同時最適化問題における共通部品情報と仮想親個体を用いた最適化手法の提案　　　　　　　　　　　　　　　
  Tomohiro Harada
  進化計算学会論文誌, Volume：9, Number：2, First page：41, Last page：52, Sep. 2018, [Reviewed], [Corresponding]
  Japanese, Scientific journal
  DOI：https://doi.org/10.11394/tjpnsec.9.41
  DOI ID：10.11394/tjpnsec.9.41, ISSN：2185-7385, ORCID：53313910
• An Audience Participation Angry Birds Platform for Social Well-Being　　　　　　　　　　　　　　　
  The 19th annual European GAME-ON Conference (GAME-ON 2018), Sep. 2018
• モーションゲームのためのユニバーサルスケルトン構築　　　　　　　　　　　　　　　
  2018 年度情報処理学会関西支部 支部大会, Sep. 2018
• キュリオシティドリブンを用いた格闘ゲームAIの提案　　　　　　　　　　　　　　　
  2018 年度情報処理学会関西支部 支部大会, Sep. 2018
• ローリングホライゾン進化的アルゴリズムを用いたペルソナ格闘ゲームAI　　　　　　　　　　　　　　　
  2018 年度情報処理学会関西支部 支部大会, Sep. 2018
• GANとCNNを用いた絵画のカラー化　　　　　　　　　　　　　　　
  2018 年度情報処理学会関西支部 支部大会, Sep. 2018
• Validation of deep features using the 1-NN algorithm for image similarity computation　　　　　　　　　　　　　　　
  Lilang Xiong; Zhenao Wei; Wenwen Ouyang; Tomohiro Harada; Ruck Thawonmas; Keiko Suzuki; Masaaki Kidachi
  Proceedings - 2018 NICOGRAPH International, NICOINT 2018, First page：81, Aug. 2018
  This paper describes a study that examines deep features by using the 1-NN algorithm in image similarity computation. This work extends our previous work that compared a number of deep-feature-extraction techniques, or feature vectors, in image-style classification. Our finding here is that the feature vector where each element is the cosine similarity between respective pair of the VGG-19 conv5-1 layer's feature maps is the most promising for computation of ukiyo-e similarity.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOINT.2018.00027
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053529315&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85053529315&origin=inward
  DOI ID：10.1109/NICOINT.2018.00027, SCOPUS ID：85053529315
• Smile with angry birds: Two smile-interface implementations　　　　　　　　　　　　　　　
  Changeun Yang; Yuxuan Jiang; Pujana Paliyawan; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2018 NICOGRAPH International, NICOINT 2018, First page：80, Aug. 2018
  This paper proposes two implementations for promoting mental well-being in Angry Birds, one of the most popular mobile games. In the first implementation, fog is introduced for hiding some parts of the game stage, and the player must smile in order to erase fog. In the second implementation, a special TNT is introduced, which can be exploded by the player's smile. We evaluate each of the two implementations by analyzing effects on the player's mental status and game satisfaction.
  International conference proceedings
  DOI：https://doi.org/10.1109/NICOINT.2018.00026
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053549636&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85053549636&origin=inward
  DOI ID：10.1109/NICOINT.2018.00026, SCOPUS ID：85053549636
• 木構造類似度を用いる多峰性遺伝的プログラミング　　　　　　　　　　　　　　　
  Tomohiro Harada
  計測自動制御学会論文集, Volume：54, Number：8, First page：640, Last page：649, Aug. 2018, [Reviewed], [Corresponding]
  Japanese, Scientific journal
  DOI：https://doi.org/10.9746/sicetr.54.640
  DOI ID：10.9746/sicetr.54.640, ISSN：0453-4654, ORCID：53313912, 共同研究・競争的資金等ID：27301250
• Deep feature extraction based on an L2-constrained combination of center and softmax loss functions for ukiyo-e image recommendation　　　　　　　　　　　　　　　
  The 1st KDD Workshop on Data Science for Digital Art History: tackling big data Challenges, Algorithms, and Systems, Aug. 2018
• Crowding distance based promising solution selection in surrogate assisted asynchronous multi-objective evolutionary algorithm　　　　　　　　　　　　　　　
  Tomohiro Harada; Misaki Kaidan; Ruck Thawonmas
  GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, First page：253, Last page：254, Jul. 2018
  This paper proposes an efficient solution selection method in a surrogate-assisted asynchronous multi-objective evolutionary algorithm. Our previous research proposed a novel multi-objective evolutionary algorithm that integrates a surrogate evaluation model with asynchronous approach, named as AELMOEA/D. AELMOEA/D constructs a surrogate model with extreme learning machine (ELM) and generates a promising solution by MOEA/D with a constructed ELM model. A generated promising solution is selected in the order of the indexes of the weighted vector of MOEA/D, and is evaluated asynchronously. In contrast to the previous method, the proposed method considers degree of search progress of each weight vector and selects a promising solution in a region where the search progress is insufficient. To evaluate the degree of the search progress, this study employs crowding distance, which is basically used in NSGA-II. To investigate the effectiveness of the proposed method, we conduct the experiment on a multi-objective optimization benchmark problem. The experimental result revealed that the proposed method can accelerate the convergence speed of the optimization without deteriorating the performance compared with the previous method.
  International conference proceedings
  DOI：https://doi.org/10.1145/3205651.3205709
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051494717&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85051494717&origin=inward
  DOI ID：10.1145/3205651.3205709, SCOPUS ID：85051494717
• Evolutionary algorithm using surrogate assisted model for simultaneous design optimization benchmark problem of multiple car structures　　　　　　　　　　　　　　　
  Hiro Ohtsuka; Tomohiro Harada; Misaki Kaidan; Ruck Thawonmas
  GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, First page：55, Last page：56, Jul. 2018
  This paper proposes a surrogate-assisted evolutionary algorithm for solving optimization problems with high calculation cost for constraint determination. The proposed method consists of CMOEA/D that extends the ability of MOEA/D to deal with constrained optimization problems and a surrogate evaluation model constructed by a machine learning, extreme learning machine (ELM). To investigate the effectiveness of the proposed method, we conduct an experiment on simultaneous design optimization benchmark problem of multiple car structures developed by Mazda Motor Corporation et al.. The experimental result revealed that the proposed method can obtain optimal solutions faster than CMOEA/D without a surrogate model.
  International conference proceedings
  DOI：https://doi.org/10.1145/3205651.3208771
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85051537061&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85051537061&origin=inward
  DOI ID：10.1145/3205651.3208771, SCOPUS ID：85051537061
• Evolutionary Algorithm Using Surrogate Assisted Model for Simultaneous Design Optimization Benchmark Problem of Multiple Car Structures　　　　　　　　　　　　　　　
  Late-Breaking Abstract in Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Jul. 2018
• Crowding Distance based Promising Solution Selection in Surrogate Assisted Asynchronous Multi-Objective Evolutionary Algorithm　　　　　　　　　　　　　　　
  Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Jul. 2018
• Adaptive Asynchrony in Semi-Asynchronous Evolutionary Algorithm Based on Performance Prediction Using Search History　　　　　　　　　　　　　　　
  Genetic and Evolutionary Computation Conference 2018 (GECCO 2018), Jul. 2018
• Potential improvement of CNN-based colorization for non-natural images　　　　　　　　　　　　　　　
  Ayumu Shinya; Kazuki Mori; Tomohiro Harada; Ruck Thawonmas
  2018 International Workshop on Advanced Image Technology, IWAIT 2018, May 2018
  This paper discusses colorization of grayscale non-natural images using convolutional neural networks (CNNs). We show that current state-of-the-art colorization methods which use deep CNNs trained on natural images do not perform well on non-natural images, such as images of ukiyo-e. We therefore propose how to improve such methods without retraining their networks.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/IWAIT.2018.8369678
• Improvement of the SLIM Spacecraft Location Estimation by Crater Matching Based on Similar Triangles and Its Improvement　　　　　　　　　　　　　　　
  Haruyuki ISHII; Akinori MURATA; Fumito UWANO; Takato TATSUMI; Yuta UMENAI; Keiki TAKADAMA; Tomohiro HARADA; Hiroyuki KAMATA; Takayuki ISHIDA; Seisuke FUKUDA; Shujiro SAWAI; Shinichiro SAKAI
  AEROSPACE TECHNOLOGY JAPAN, THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, Volume：17, First page：69, Last page：78, May 2018, [Reviewed]
  Japanese, Scientific journal
  DOI：https://doi.org/10.2322/astj.JSASS-D-17-00011
  DOI ID：10.2322/astj.JSASS-D-17-00011, ISSN：1884-0477, J-Global ID：201802217977110700, ORCID：53313879
• 複数車種の同時最適化問題に対する代替評価モデルを用いた進化計算手法　　　　　　　　　　　　　　　
  第14回進化計算研究会, Mar. 2018
• Sleep Stage Estimation Comparing Own Past Heartrate or Others' Heartrate　　　　　　　　　　　　　　　
  Tajima, Yusuke; Uwano, Fumito; Murata, Akinori; Harada, Tomohiro; Takadama, Keiki
  SICE Journal of Control, Measurement, and System Integration, Volume：11, Number：1, First page：32, Last page：39, Mar. 2018, [Reviewed]
  The Society of Instrument and Control Engineers, English, Scientific journal
  DOI：https://doi.org/10.9746/jcmsi.11.32
  DOI ID：10.9746/jcmsi.11.32, ISSN：1882-4889, ORCID：53313895
• Sleep Stage Re-Estimation Method According To Sleep Cycle Change　　　　　　　　　　　　　　　
  The AAAI 2018 Spring Symposium on "Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being", Mar. 2018
• A Personalized Method for Calorie Consumption Assessment　　　　　　　　　　　　　　　
  The AAAI 2018 Spring Symposium on "Beyond Machine Intelligence: Understanding Cognitive Bias and Humanity for Well-Being", Mar. 2018
• Sleep stage re-estimation method according to sleep cycle change　　　　　　　　　　　　　　　
  Yusuke Tajima; Akinori Murata; Tomohiro Harada; Keiki Takadama
  AAAI Spring Symposium - Technical Report, Volume：2018-, First page：280, Last page：284, 2018
  This paper focuses on a sleep cycle, and improves the problem which an estimation accuracy of Real-Time Sleep Stage Estimation Method(RSSE) when it estimates a sleep stage on real time. Concretely, the proposed method re-estimates the sleep stage immediately after first sleep cycle since going to bed for the problem which decreases the correct rate of the sleep stage estimated by RSSE as time passes since going to bed. From the human subject experiments, the following implications have been revealed: (1) the correct rate improved by re-estimation in 8 cases out of 9 cases. (2) when the sleep cycle is long, it is possible to calculate the sleep cycle from the same subject’s past sleeping information and if it is used, the estimation accuracy is improved for all cases.
  AI Access Foundation, English, International conference proceedings
  SCOPUS ID：85102595535
• A personalized method for calorie consumption assessment　　　　　　　　　　　　　　　
  Yunshi Liu; Pujana Paliyawan; Takahiro Kusano; Tomohiro Harada; Ruck Thawonmas
  AAAI Spring Symposium - Technical Report, Volume：2018-March, First page：247, Last page：252, 2018
  This paper proposes an image-processing-based method for personalization of calorie consumption assessment during exercising. An experiment is carried out where several actions are required in an exercise called broadcast gymnastics, especially popular in Japan and China. We use Kinect, which captures body actions by separating the body into joints and segments that contain them, to monitor body movements to test the velocity of each body joint and capture the subject’s image for calculating the mass of each body joint that differs for each subject. By a kinetic energy formula, we obtain the kinetic energy of each body joint, and calories consumed during exercise are calculated in this process. We evaluate the performance of our method by benchmarking it to Fitbit, a smart watch well-known for health monitoring during exercise. The experimental results in this paper show that our method outperforms a state-of-the-art calorie assessment method, which we base on and improve, in terms of the error rate from Fitbit’s ground-truth values.
  International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85072969664&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85072969664&origin=inward
  SCOPUS ID：85072969664
• Potential Improvement of CNN-based Colorization for Non-natural Images　　　　　　　　　　　　　　　
  The International Workshop on Advanced Image Technology 2018 (IWAIT 2018), Jan. 2018
• Intelligent assistant for providing instructions and recommending motions during full-body motion gaming　　　　　　　　　　　　　　　
  Jorge Arturo Morán Bravo; Pujana Paliyawan; Tomohiro Harada; Ruck Thawonmas
  2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017, Dec. 2017
  This paper presents a system that encourages players to use their body segments in a balance fashion and perform more various motions. To achieve a healthy status, the balance in the use of body segments is imperative. In general motion games, the user faces problems in memorization of motions or performing of repetitive movements, leading to an unbalanced use of body segments. This paper proposes a solution for these problems, and particularly we focus on the benefits of having an intelligent assistant in full-body motion games for giving instructions, training and recommendation of a variation of movements. Our development consists of two major modules: a during-gameplay motion recommender and a pre-gameplay instructor.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/GCCE.2017.8229403
• Towards adaptive motion gaming AI with player's behavior modeling for health promotion　　　　　　　　　　　　　　　
  Takahiro Kusano; Pujana Paliyawan; Tomohiro Harada; Ruck Thawonmas
  2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017, Dec. 2017
  This paper proposes a motion-gaming AI for health promotion that can adapt to the player's behavior change in an effective manner. Through modeling of the player's behavior and predicting of their counteraction, this AI learns how its actions can induce its opponent player to move. The proposed AI aims at suppressing health risks associated with motion gaming, by improving balancedness in use of body segments, as well as at increasing the level of calories consumption.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/GCCE.2017.8229399
• Feature extraction of gameplays for similarity calculation in gameplay recommendation　　　　　　　　　　　　　　　
  Kazuki Mori; Suguru Ito; Tomohiro Harada; Ruck Thawonmas; Kyung-Joong Kim
  2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings, Dec. 2017
  This paper proposes a method for extraction of relevant features that represent a gameplay and are needed in gameplay recommendation. In our work, content based filtering (CBF) is adopted as the recommender algorithm. CBF exploits a heuristic that the user's previous ratings of items, gameplay clips in our case, can be used to derive the rating of an unrated similar item. In this work, in order to calculate the similarity between a pair of gameplays, a kind of autoencoder called Denoising Autoencoder is employed. Our experimental results confirm that the method can successfully extract features, based on which the resulting similarity between a pair of gameplays matches with their content and human perception.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/IWCIA.2017.8203580
• Multimodal genetic programming by using tree structure similarity clustering　　　　　　　　　　　　　　　
  Shubu Yoshida; Tomohiro Harada; Ruck Thawonmas
  2017 IEEE 10th International Workshop on Computational Intelligence and Applications, IWCIA 2017 - Proceedings, Dec. 2017
  This paper proposes a multimodal genetic programming (GP) that incorporates a clustering of a population based on the tree structure similarity into GP and simultaneously acquires multiple local optimal solutions including a global optimal solution. The multimodal optimization problem aims to acquire not only a global optimal solution but also multiple local optimal solutions in a single optimization process. In general, although continuous real-valued optimizations are mainly targeted for multimodal optimization problems, problems with other solution structures, like a program in GP, have not been dealt with. This paper designs a multimodal program optimization problem that has a global and a local optimal solution and proposes a multimodal GP to acquires multiple local optimal programs including a global optimal one. Concretely, the proposed method separates the population into several clusters based on the similarity of tree structure, which is used as program expression in GP. Then, local optimum programs with different structure are acquired by optimizing each cluster separately. In order to investigate the effectiveness of the proposed method, we compare the proposed method with a simple GP without clustering on the designed multimodal GP benchmark. The experimental result reveals that the proposed method can acquire both the global and the local optimal programs at the same time.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/IWCIA.2017.8203566
• 半非同期進化法における探索履歴を用いた性能予測に基づく非同期性の適応的調整半非同期進化法における探索履歴を用いた性能予測に基づく非同期性の適応的調整　　　　　　　　　　　　　　　
  進化計算シンポジウム2017, Dec. 2017
• 遺伝的アルゴリズムによる感情とシチュエーションを想起させる川柳の自動生成　　　　　　　　　　　　　　　
  計測自動制御学会 システム・情報部門 学術講演会 2017（SSI2017）, Nov. 2017
• General Video Game Playingにおける遺伝的アルゴリズムを用いたパラメータ最適化　　　　　　　　　　　　　　　
  計測自動制御学会 システム・情報部門 学術講演会 2017（SSI2017）, Nov. 2017
• 睡眠周期の変化に着目したリアルタイム睡眠段階再推定法　　　　　　　　　　　　　　　
  ヘルスケア・医療情報通信技術研究会（MICT）ヘルスケア・医療情報通信技術研究会（MICT）, Nov. 2017
• Procedural generation of angry birds fun levels using pattern-struct and preset-model　　　　　　　　　　　　　　　
  Yuxuan Jiang; Tomohiro Harada; Ruck Thawonmas
  2017 IEEE Conference on Computational Intelligence and Games, CIG 2017, Oct. 2017
  In this paper, we describe our design of a generator for automatically generating fun levels in the famous game Angry Birds and its clone games. In particular, we aim at generation of character-sequence levels. In order to generate fun levels, we propose a pattern-struct approach and a preset- model approach. The pattern-struct approach generates each time different appearance for one of the alphabetical letters, numeral numbers, or some symbols. The preset-model approach is used for increasing the legibility and diversity, where models are built in advance for some capital letters and numbers. Our level generator, called Funny Quotes, was the winner of the Fun Track of the CIG 2016 Level Generation Competition held in 2016 IEEE Conference on Computational Intelligence and Games. After raising issues residing in Funny Quotes through user-evaluation results in terms of legibility of characters in generated levels and of playability of those levels, we propose and evaluate new mechanisms for ensuring the disparity in difficulty among easy, normal, and hard levels for the 2017 competition.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/CIG.2017.8080429
• Machine-code program evolution by genetic programming using asynchronous reference-based evaluation through single-event upset in on-board computer
  Tomohiro Harada; Keiki Takadama
  Journal of Robotics and Mechatronics, Volume：29, Number：5, First page：808, Last page：818, Oct. 2017, [Reviewed], [Lead, Corresponding]
  This study proposes a novel genetic programming method using asynchronous reference-based evaluation (called AREGP) to evolve computer programs through single-event upsets (SEUs) in the on-board computer in space missions. AREGP is an extension of Tierra-based asynchronous genetic programming (TAGP), which was proposed in our previous study. It is based on the idea of the biological simulator, Tierra, where digital creatures are evolved through bit inversions in a program. AREGP not only inherits the advantages of TAGP but also overcomes its limitation, i.e., TAGP cannot select good programs for evolution without an appropriate threshold. Specifically, AREGP introduces an archive mechanism to maintain good programs and a reference-based evaluation by using the archive for appropriate threshold selection and removal. To investigate the effectiveness of the proposed AREGP, simulation experiments are performed to evolve the assembly language program in the SEU environment. In these experiments, the PIC instruction set, which is carried on many types of spacecraft, is used as the evolved assembly program. The experimental results revealed that AREGP cannot only maintain the correct program through SEU with high occurrence rate, but is also better at reducing the size of programs in comparison with TAGP. Additionally, AREGP can achieve a shorter execution step and smaller size of programs, which cannot be achieved by TAGP.
  Fuji Technology Press, English, Scientific journal
  DOI：https://doi.org/10.20965/jrm.2017.p0808
  DOI ID：10.20965/jrm.2017.p0808, ISSN：1883-8049, ORCID：60076110, SCOPUS ID：85031900306
• Feature extraction of game plays for procedural play generation　　　　　　　　　　　　　　　
  Kazuki Mori; Ayumu Shinya; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2017 NICOGRAPH International, NICOInt 2017, Sep. 2017
  This paper proposes a feature extraction method from a game play (play). To recommend plays to spectators, such feature extraction is required. Our results show that the proposed method successfully extracted features from plays.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/NICOInt.2017.37
• Automatic generation of game plays considering the play arc by the AI in a fighting game　　　　　　　　　　　　　　　
  Suguru Ito; Makoto Ishihara; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2017 NICOGRAPH International, NICOInt 2017, Sep. 2017
  In this paper, we propose AIs using Monte-Carlo Tree Search (MCTS) for generating game plays considering the play arc. Our results show that the proposed method is effective for creating such game plays in a fighting game.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/NICOInt.2017.38
• Object-specific style transfer based on feature map selection using CNNs　　　　　　　　　　　　　　　
  Ayumu Shinya; Nguyen Duc Tung; Tomohiro Harada; Ruck Thawonmas
  Proceedings - 2017 NICOGRAPH International, NICOInt 2017, Sep. 2017
  We propose a method for transferring an arbitrary style to only a specific object in an image. Style transfer is the process of combining the content of an image and the style of another image into a new image. Our results show that the proposed method can realize style transfer to specific object.
  Institute of Electrical and Electronics Engineers Inc., English
  DOI：https://doi.org/10.1109/NICOInt.2017.39
• 木構造類似度を用いる多峰性遺伝的プログラミングにおける交叉法の検証　　　　　　　　　　　　　　　
  第13回進化計算研究会, Sep. 2017
• 代替評価モデルを用いる非同期多目的進化計算法における混雑度距離による有望解選択　　　　　　　　　　　　　　　
  第13回進化計算研究会, Sep. 2017
• A Study of Self-Adaptive Semi-Asynchronous Evolutionary Algorithm on Multi-Objective Optimization Problem　　　　　　　　　　　　　　　
  ACM Workshop on Parallel and Distributed Evolutionary Inspired Method (PDEIM) in Genetic and Evolutionary Computation Conference 2017 (GECCO2017), Jul. 2017
• Integrating Surrogate Evaluation Model and Asynchronous Evolution in Multi-Objective Evolutionary Algorithm for Expensive and Different Evaluation Time　　　　　　　　　　　　　　　
  ACM Workshop on Parallel and Distributed Evolutionary Inspired Method (PDEIM) in Genetic and Evolutionary Computation Conference 2017 (GECCO2017), Jul. 2017
• 多目的最適化問題における評価時間の偏りが半非同期進化法に与える影響の分析　　　　　　　　　　　　　　　
  第11回コンピューテーショナル・インテリジェンス研究会, Jun. 2017
• Performance Comparison of Parallel Asynchronous Multi-Objective Evolutionary Algorithm with Different Asynchrony　　　　　　　　　　　　　　　
  IEEE Congress on Evolutionary Computation 2017 (CEC2017), Jun. 2017
• Adaptive Motion Gaming AI for Health Promotion　　　　　　　　　　　　　　　
  AAAI 2017 Spring Symposium, Mar. 2017
• Sleep Stage Estimation Based on Appriximate Heartrate Calculated from Other Persons　　　　　　　　　　　　　　　
  AAAI 2017 Spring Symposium, Mar. 2017
• Sleep stage estimation based on approximate heartrate calculated from other persons　　　　　　　　　　　　　　　
  Yusuke Tajima; Tomohiro Harada; Keiki Takadama
  AAAI Spring Symposium - Technical Report, Volume：SS-17-01, First page：734, Last page：739, 2017
  This paper focuses on the sleep stage estimation method based on the approximate heartrate calculated from one person, and improves its estimation accuracy by employing the approximate heartrate calculated from other persons. Concretely, the proposed approximate heartrate is a weighted summation of the approximate heartrate calculated from other persons. Through the human subject experiments, the following implications have been revealed: (1) the accuracy of the sleep stage estimation method based on the approximate heartrate calculated from other persons is higher than that of the conventional method based on the approximate heartrate calculated from one person
  and (2) the accuracy of the sleep stage estimation increases as the number of the heartbeat data of other persons for calculating the approximate heartrate increases, i.e., the accuracy of the sleep stage estimation employing the heartbeat data of the six other persons is higher than of two other persons, one other person, and none of other person.
  AI Access Foundation, English, International conference proceedings
  SCOPUS ID：85028693791
• プレイヤー適応型健康促進の Motion Gaming AI　　　　　　　　　　　　　　　
  Tomohiro Harada
  第 79 回全国大会講演論文集, 2017
  Scientific journal
  ORCID：53313917
• The Characteristics Of Asthma Patients In Er Visit　　　　　　　　　　　　　　　
  Ohta, Shin; Hirai, Kuniaki; Jinno, Megumi; Homma, Tetsuya; Tanaka, Akihiko; Sato, Harna; Uno, Tomoki; Fujiwara, Akiko; Uchida, Yoshitaka; Manabe, Ryo; others
  B25. ASTHMA EPIDEMIOLOGY: EXACERBATIONS, ADMISSIONS, READMISSIONS, AND ED VISITS, First page：A3033, Last page：A3033, 2017
  American Thoracic Society
  ORCID：53313900
• 睡眠周期の変化に着目したリアルタイム睡眠段階再推定法 (ヘルスケア・医療情報通信技術)　　　　　　　　　　　　　　　
  Tomohiro Harada
  電子情報通信学会技術研究報告= IEICE technical report: 信学技報, 2017
  Scientific journal
  ORCID：53313897
• Description for the Funny Quotes ft. Dominoes Generator　　　　　　　　　　　　　　　
  Jiang, Yuxuan; Ishii, Ryota; Harada, Tomohiro; Thawonmas, Ruck
  2017
  Scientific journal
  ORCID：53313878
• 文字, 数字, 記号列による Angry Birds の面白いステージの自動生成　　　　　　　　　　　　　　　
  Tomohiro Harada
  第 79 回全国大会講演論文集, 2017
  Scientific journal
  ORCID：53313923
• CNN ベースのカラー化手法の検証とその改善法の提案　　　　　　　　　　　　　　　
  Tomohiro Harada
  2017 年度 情報処理学会関西支部 支部大会 講演論文集, 2017
  Scientific journal
  ORCID：53313918
• 畳み込みニューラルネットワークによる特定部分へのスタイル転移　　　　　　　　　　　　　　　
  Tomohiro Harada
  第 79 回全国大会講演論文集, 2017
  Scientific journal
  ORCID：53313914
• Angry Birds におけるドミノステージの難易度調整　　　　　　　　　　　　　　　
  Tomohiro Harada
  2017 年度 情報処理学会関西支部 支部大会 講演論文集, 2017
  Scientific journal
  ORCID：53313908
• AI for game spectators: Rise of PPG　　　　　　　　　　　　　　　
  Ruck Thawonmas; Tomohiro Harada
  AAAI Workshop - Technical Report, Volume：WS-17-01 - WS-17-15, First page：1032, Last page：1033, 2017
  This position paper describes an AI application for game spectators, e.g., those watching Twitch. The aim of this application is to automatically generate game plays by non- player characters - not human players ..and recommend those plays to spectators. The generation part leads to development of a new field: procedural play generation (PPG). The recommendation part requires new techniques in recommender systems (RS) for incorporation of play content into RS to obtain promising recommendation results. Rather than proposing solutions to all relevant topics, this paper aims at drawing attention to this new field and serves as a seed for discussion and collaboration among the readers, workshop participants, and authors.
  International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85032787774&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85032787774&origin=inward
  SCOPUS ID：85032787774
• Procedural play generation according to play arcs using Monte-Carlo tree search　　　　　　　　　　　　　　　
  Suguru Ito; Makoto Ishihara; Marco Tamassia; Tomohiro Harada; Ruck Thawonmas; Fabio Zambetta
  18th International Conference on Intelligent Games and Simulation, GAME-ON 2017, First page：67, Last page：71, 2017
  More than a million spectators watch game streaming platforms such as Twitch every month. This phenomenon suggests video games are a powerful entertainment media not just for players but for spectators as well. Since each spectator has personal preferences, customized spectator-specific game plays are arguably a promising option to increase the entertainment value of video games streaming. In this paper, we propose an Artificial Intelligence (AI) that automatically generates game plays according to play arcs using Monte Carlo Tree Search (MCTS). In particular, we concentrate on fighting games and drive MCTS to achieve specific hitpoints differences between characters at different moments of the game. Our preliminary results show that the proposed AI can generate game plays following the desired transition of game progress.
  International conference proceedings
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047222107&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85047222107&origin=inward
  SCOPUS ID：85047222107
• Segmentation Mask Refinement Using Image Transformations　　　　　　　　　　　　　　　
  Tung Duc Nguyen; Ayumu Shinya; Tomohiro Harada; Ruck Thawonmas
  IEEE ACCESS, Volume：5, First page：26409, Last page：26418, 2017, [Reviewed]
  This paper discusses object proposal generation, which is a crucial step of instance-level semantic segmentation (instance segmentation). Known as a challenging computer vision task, the instance segmentation requires jointly detecting and segmenting individual instances of objects in an image. A common approach to this task is first to propose a set of class-agnostic object candidates in the forms of segmentation masks, which represent both object locations and boundaries, and then to perform classification on each object candidate. In this paper, we propose an effective refinement process that employs image transformations and mask matching to increase the accuracy of object segmentation masks. The proposed refinement process is applied to three state-of-the-art object proposal methods (DeepMask, SharpMask, and FastMask), and is evaluated on two standard benchmarks (Microsoft COCO and PASCAL VOC). Both the quantitative and qualitative results show the effectiveness of the process across various experimental settings.
  IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, English, Scientific journal
  DOI：https://doi.org/10.1109/ACCESS.2017.2772269
  DOI ID：10.1109/ACCESS.2017.2772269, ISSN：2169-3536, ORCID：60076131, SCOPUS ID：85034254465, Web of Science ID：WOS:000418881100030
• AI for Game Spectators: Rise of PPG　　　　　　　　　　　　　　　
  AAAI 2017 Workshop on What's next for AI on games, 2017
• Analysis of Relationship between the Player's Behavior Change and the Effectiveness of a Health Promotion AI　　　　　　　　　　　　　　　
  NICOGRAPH international 2017, 2017
• 心拍数変動の類似性を考慮したリアルタイム睡眠段階推定　　　　　　　　　　　　　　　
  第31回人工知能学会全国大会, 2017
• アメーバからヒントを得た数理モデルを用いた格闘ゲームAIの提案　　　　　　　　　　　　　　　
  第79回情報処理学会全国大会, 2017
• 文字，数字，記号列によるAngry Birdsの面白いステージの自動生成　　　　　　　　　　　　　　　
  第79回情報処理学会全国大会, 2017
• 格闘ゲームにおける多様性のあるゲームプレイのAIによる自動生成　　　　　　　　　　　　　　　
  第44回知能システムシンポジウム, 2017
• 覚醒と浅睡眠に着目した圧力センサに基づく非侵襲的睡眠段階推定とその精度向上　　　　　　　　　　　　　　　
  第44回知能システムシンポジウム, 2017
• Improving Accuracy of Real-time Sleep Stage Estimation by Considering Personal Sleep Feature
  原田 智広; 川嶋 隆宏; 森島 守人; 高玉 圭樹
  Volume：116, Number：224, First page：63, Last page：68, Sep. 2016
  Japanese
  ISSN：0913-5685, CiNii Articles ID：40020960910
• Predicting the opponent's action using the k-nearest neighbor algorithm and a substring tree structure　　　　　　　　　　　　　　　
  Yuto Nakagawa; Kaito Yamamoto; Chu Chun Yin; Tomohiro Harada; Ruck Thawonmas
  2015 IEEE 4th Global Conference on Consumer Electronics, GCCE 2015, First page：533, Last page：534, Feb. 2016
  This paper proposes a technique for predicting the opponent's next action accurately by combining the k-nearest neighbor algorithm and a substring tree structure. Furthermore, our AI, employing the proposed technique, is enhanced by the implementation of Boltzmann equation control. The proposed method and the enhanced AI are evaluated on a fighting game AI competition platform, and their results attest to their effectiveness.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2015.7398673
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964939955&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84964939955&origin=inward
  DOI ID：10.1109/GCCE.2015.7398673, SCOPUS ID：84964939955
• Improving heuristic search for RTS-game unit micromanagement using reinforcement learning　　　　　　　　　　　　　　　
  Supaphon Kamon; Tung Due Nguyen; Tomohiro Harada; Ruck Thawonmas; Ikuko Nishikawa
  2015 IEEE 4th Global Conference on Consumer Electronics, GCCE 2015, First page：25, Last page：26, Feb. 2016
  This paper proposes a method that uses reinforcement learning to improve heuristic search for unit micromanagement in real-time strategy (RTS) games. In the RTS game, unit micromanagement describes the detailed control of units, or, in other words, how the player controls their units. It decides all the commands that the player gives to their units such as the position, movement, abilities. One of the most commonly used algorithms for unit micromanagement is heuristic search. Due to the fact that the RTS game has large number of states and large action space, the heuristic search algorithm has to rely on evaluation methods that only search with a certain limited depth. We therefore apply reinforcement learning to achieve an evaluation method with high accuracy.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2015.7398675
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964981876&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84964981876&origin=inward
  DOI ID：10.1109/GCCE.2015.7398675, SCOPUS ID：84964981876
• Procedural generation of angry birds levels that adapt to the player's skills using genetic algorithm　　　　　　　　　　　　　　　
  Misaki Kaidan; Chun Yin Chu; Tomohiro Harada; Ruck Thawonmas
  2015 IEEE 4th Global Conference on Consumer Electronics, GCCE 2015, First page：535, Last page：536, Feb. 2016
  This paper proposes a procedural generation method that automatically creates game levels for Angry Birds, a famous mobile game, using genetic algorithm. By adjusting the parameters of the genetic algorithm according to the player's gameplay results, our proposed method can generate game levels that adapt to the player's skills. Our experiment proves that the proposed method is able to procedurally generate game levels that befit the player's skill.
  International conference proceedings
  DOI：https://doi.org/10.1109/GCCE.2015.7398674
  Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964989103&origin=inward
  Scopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84964989103&origin=inward
  DOI ID：10.1109/GCCE.2015.7398674, SCOPUS ID：84964989103
• Personalized real-time sleep stage from past sleep data to today’s sleep estimation
  Tajima, Y.; Harada, T.; Sato, H.; Takadama, K.
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：9735, 2016
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Scientific journal
  DOI：https://doi.org/10.1007/978-3-319-40397-7_48
  DOI ID：10.1007/978-3-319-40397-7_48, ORCID：60076142, SCOPUS ID：84978828766
• 建築物の生成ルールと中華風や和風の複数のモデルを用いた Angry Birds のレベル自動生成　　　　　　　　　　　　　　　
  Tomohiro Harada
  第 78 回全国大会講演論文集, 2016
  Scientific journal
  ORCID：53313868
• Comparative Analysis of Reinforcement Learning and Evolutionary Strategy in General Video Game Playing　　　　　　　　　　　　　　　
  Chu, Chun-Yin; Ito, Suguru; Harada, Tomohiro; Thawonmas, Ruck
  情報処理学会第 78 回全国大会, Volume：5, First page：09, Last page：09, 2016
  Scientific journal
  ORCID：53313845
• Real-time sleep stage estimation from biological data with trigonometric function regression model　　　　　　　　　　　　　　　
  Tomohiro Harada; Fumito Uwano; Takahiro Komine; Yusuke Tajima; Takahiro Kawashima; Morito Morishima; Keiki Takadama
  AAAI Spring Symposium - Technical Report, Volume：SS-16-01 - 07, First page：348, Last page：353, Jan. 2016
  Copyright © 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This paper proposes a novel method to estimate sleep stage in real-time with a non-contact device. The proposed method employs the trigonometric function regression model to estimate prospective heart rate from the partially obtained heart rate and calculates the sleep stage from the estimated heart rate. This paper conducts the subject experiment and it is revealed that the proposed method enables to estimate the sleep stage in realtime, in particular the proposed method has the equivalent estimation accuracy as the previous method that estimates the sleep stage according to the entire heart rate during sleeping.
  SCOPUS ID：84980047676
• Evolutionary multi-objective route and fleet assignment optimisation for regular and non-regular flights　　　　　　　　　　　　　　　
  Takadama, Keiki; Jinba, Takahiro; Harada, Tomohiro; Sato, Hiroyuki
  International Journal of Automation and Logistics, Volume：2, Number：1-2, First page：122, Last page：152, 2016, [Reviewed]
  Inderscience Publishers (IEL), English, Scientific journal
  DOI：https://doi.org/10.1504/IJAL.2016.074936
  DOI ID：10.1504/IJAL.2016.074936, ORCID：53313835
• 対戦格闘ゲームにおけるゲームAI や操作法の違いがプレイヤーの感じる面白さに与える影響の分析　　　　　　　　　　　　　　　
  石原 誠; 宮崎 泰地; 原田 智広; ターウォンマット ラック
  情報処理学会論文誌, Volume：57, Number：11, First page：2414, Last page：2425, 2016, [Reviewed]
  本稿では，対戦格闘ゲームにおけるゲームAI（AI）や操作法がプレイヤの感じる面白さに与える影響について分析する．対戦格闘ゲームには，キーボードなどの指先による操作と，Kinectを用いて体の動きで操作する方法がある．プレイヤがいずれの操作においても楽しく対戦格闘ゲームをプレイするためには，プレイヤと互角に戦うようなAIが必要である．また，それを実現させるためには強さをある程度持ったAIが必要である．本稿では，UCTをノード選択における戦略としたモンテカルロ木探索，ルーレット選択，ルールベースの手法を組み合わせることで，先述したAIを開発する．このAIをベースにし，UCTの評価関数を改変することによってプレイヤに合わせて強さを調整（難易度調整）するAIを開発する．そして，AIや操作法がプレイヤの感じる面白さに与える影響を，キーボード，Kinectのそれぞれの操作において分析する．対戦格闘ゲームの国際AI大会のプラットフォームとして利用されているFightingICEを用いた被験者実験より，難易度調整はプレイヤがより楽しんで対戦格闘ゲームをプレイするための重要な要素であり，特にKinectにおいて顕著な効果が示された．In this paper, we analyze effects of AIs and interfaces to players' enjoyment in fighting games. There are two input interfaces in fighting games. One is finger-control interface such as the keyboard or gamepad, and the other is body-movement-control interface like Kinect. In order to have players enjoy playing fighting games in both input interfaces, AIs are need that evenly fight against their opponent human players. To implement such AIs, it is also necessary to have sufficiently strong AIs to be based upon. In this paper, first, we attempt to make a latter AI, called pAI, by combining MCTS with UCT (used in MCTS's selection criteria), roulette selection, and rule-base. Next, based on pAI, by changing its UCT evaluation function, we develop eAI, an AI that dynamically adjusts its strength to that of its current player in the game. Finally, we analyze effects of both AIs and keyboard as well as Kinect interfaces to players' enjoyment. The results of our experiments using FightingICE, a fighting game platform recently used in a number of game AI competitions, show that adjustment of AIs' strength is an important factor for the player to play the game with more fun.
  Japanese, Scientific journal
  ISSN：1882-7764, CiNii Articles ID：170000131097, CiNii Books ID：AN00116647
• Promoting Machine-code Program Evolution in Asynchronous Genetic Programming　　　　　　　　　　　　　　　
  Tomohiro Harada; Keiki Takadama; Hiroyuki Sato
  SICE Journal of Control, Measurement, and System Integration (JCMSI), Volume：9, Number：2, First page：93, Last page：102, 2016, [Reviewed], [Lead, Corresponding]
  This paper focuses on an asynchronous program evolution in evolutionary computation, which is hard to evolve programs effectively unlike a synchronous program evolution that evolves individuals effectively by selecting good parents after evaluations of all individuals in each generation. To tackle this problem, we explore the mechanism that can promote an asynchronous program evolution by selecting a good individual without waiting for evaluations of all individuals. For this purpose, this paper investigates the effectiveness of the proposed mechanisms in genetic programing (GP) domain by evaluating it in the two types of problems, the arithmetic and the Boolean problems. Through the intensive experiments of the eight kinds of testbeds under the two types of problems, the following implications have been revealed: (1) the program asynchronously evolved with the proposed mechanism can be completed with mostly the same or shorter execution steps than the program asynchronously evolved without the proposed mechanism, in particular the proposed mechanism improves the performance of the asynchronous evolution in the arithmetic problems; and (2) the program asynchronously evolved with the proposed mechanism can be completed with mostly the same or shorter execution steps than the program evolved by the conventional GP.
  The Society of Instrument and Control Engineers, English, Scientific journal
  DOI：https://doi.org/10.9746/jcmsi.9.93
  DOI ID：10.9746/jcmsi.9.93, ISSN：1882-4889, CiNii Articles ID：130005142525, ORCID：53313841
• 非同期進化的アルゴリズムにおける解の性質と評価時間の関係性による影響の分析　　　　　　　　　　　　　　　
  Tomohiro Harada
  進化計算学会論文誌, Volume：7, Number：2, First page：46, Last page：55, 2016, [Reviewed], [Lead, Last, Corresponding]
  Japanese, Scientific journal
  ORCID：53313849
• オープンループサーチを用いた対戦格闘ゲーム AI の提案　　　　　　　　　　　　　　　
  平成28 年度情報処理学会関西支部大会, 2016
• Position-based Reinforcement Learning Biased MCTS for General Video Game Playing　　　　　　　　　　　　　　　
  2016 IEEE Computational Intelligence and Games (CIG2016), 2016
• Applying and Improving Monte-Carlo Tree Search in a Fighting Game AI　　　　　　　　　　　　　　　
  Proceedings of the 13th International Conference on Advances in Computer Entertainment Technology (ACE 2016), 2016
• Application of Monte-Carlo Tree Search in a Fighting Game AI　　　　　　　　　　　　　　　
  Proceedings of the 5th IEEE Global Conference on Consumer Electronics (GCCE 2016), 2016
• Efficient Implementation of Breadth First Search for General Video Game Playing　　　　　　　　　　　　　　　
  Proceedings of the 5th IEEE Global Conference on Consumer Electronics (GCCE 2016), 2016
• An Improvement of Matrix Factorization with Bound Constraints for Recommender Systems　　　　　　　　　　　　　　　
  2016 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), 2016
• Procedural Generation of Angry Birds Levels with Adjustable Difficulty　　　　　　　　　　　　　　　
  Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC 2016), 2016
• 非同期性を適応的に制御する半非同期進化的アルゴリズムの検討　　　　　　　　　　　　　　　
  進化計算シンポジウム2016, 2016
• 非同期リファレンス評価を用いる進化的アルゴリズムの選択・削除法の改良　　　　　　　　　　　　　　　
  計測自動制御学会 システム・情報部門 学術講演会 2016（SSI2016）, 2016
• ゲームAI大会を通した格闘ゲームプラットフォームとそのゲームAIの分析　　　　　　　　　　　　　　　
  ゲーム学会第15回全国大会, 2016
• 遺伝的アルゴリズムによるプレイヤーのスキルに適したAngry Birdsのレベル自動生成　　　　　　　　　　　　　　　
  計測自動制御学会 システム・情報部門 学術講演会 2016（SSI2016）, 2016
• 生体リズムに連動した音と音色の違いが睡眠に及ぼす影響　　　　　　　　　　　　　　　
  山木 清志; 植屋 夕輝; 石原 淳; 森島 守人; 原田 智広; 高玉 圭樹; 角谷 寛
  日本睡眠学会定期学術集会プログラム・抄録集, Volume：40回, First page：255, Last page：255, Jul. 2015
  (一社)日本睡眠学会, Japanese
  医中誌Web ID：2016017120
• Kinect を用いた対戦格闘ゲームにおけるユーザの運動量を向上させる AI の探求　　　　　　　　　　　　　　　
  Tomohiro Harada
  2015 年度 情報処理学会関西支部 支部大会 講演論文集, 2015
  Scientific journal
  ORCID：53313857
• 遺伝的アルゴリズムのパラメータ調整によるプレイヤーのレベルに適した Angry Birds のステージ自動生成　　　　　　　　　　　　　　　
  Tomohiro Harada
  2015 年度 情報処理学会関西支部 支部大会 講演論文集, 2015
  Scientific journal
  ORCID：53313848
• Assembly Language Program Evolution in Tierra-based On-Board Computer through Single Event Upset　　　　　　　　　　　　　　　
  Harada, Tomohiro; Takadama, Keiki
  International Journal of Engineering Science and Innovative Technology (IJESIT), Volume：4, Number：4, First page：27, Last page：42, 2015, [Reviewed]
  English, Scientific journal
  ORCID：53313889
• Toward Robustness Against Environmental Change Speed by Artificial Bee Colony Algorithm based on Local Information Sharing　　　　　　　　　　　　　　　
  2015 IEEE Congress on Evolutionary Computation (CEC2015), 2015
• 階層型進化計算を用いた動的航空機着陸経路スケジューリング　　　　　　　　　　　　　　　
  第42回知能システムシンポジウム, 2015
• Estimating Surrounding Symptom Level of Dementia Person by Sleep Stage　　　　　　　　　　　　　　　
  The Ninth International Symposium on Medical Information and Communication Technology (ISMICT 2015), 2015
• Adjusting SLIM Spacecraft Location Estimation to Crater Detection for High Precision and Computational Time Reduction　　　　　　　　　　　　　　　
  The 30th International Symposium on Space Technology and Science (ISTS2015), 2015
• Towards Ambient intelligence System for Good Sleep By Sound Adjusted to Heartbeat and Respiration　　　　　　　　　　　　　　　
  The AAAI 2015 Spring Symposia, Ambient Intelligence for Health and Cognitive Enhancement, AAAI (The Association for the Advancement of Artificial Intelligence), 2015
• Sightseeing Plan Recommendation System using Sequential Pattern Mining based on Adjacent Activities　　　　　　　　　　　　　　　
  The 10th Asian Control Conference 2015 (ASCC2015), 2015
• Investigating Kinect-based Fighting Game AIs That Encourage Their Players to Use Various Skills　　　　　　　　　　　　　　　
  2015 IEEE 4th Global Conference on Consumer Electronics (GCCE2015), 2015
• 非同期進化的アルゴリズムにおける解と評価時間の関係性による影響の分析　　　　　　　　　　　　　　　
  第9回 進化計算シンポジウム 2015, 2015
• 仮想空間における滞在時間を用いたコンテンツベース推薦手法の提案　　　　　　　　　　　　　　　
  2015年度情報処理学会関西支部支部大会, 2015
• 対戦型格闘ゲームにおけるk-substring tree構造を用いた相手の行動予測と予測精度の向上　　　　　　　　　　　　　　　
  2015年度情報処理学会関西支部支部大会, 2015
• Biasing Monte-Carlo Rollouts with Potential Field in General Video Game Playing　　　　　　　　　　　　　　　
  2015年度情報処理学会関西支部支部大会, 2015
• 対戦型ゲームAI大会におけるゲームバランスの分析　　　　　　　　　　　　　　　
  電気学会九州支部沖縄支所講演会, 2015
• What is Needed to Promote an Asynchronous Program Evolution in Genetic Programing?　　　　　　　　　　　　　　　
  Learning and Intelligent Optimization Conference (LION8), Lecture Notes in Computer Science, Feb. 2014
• Asynchronous evolution by reference-based evaluation: Tertiary parent selection and its archive　　　　　　　　　　　　　　　
  Harada, T.; Takadama, K.
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：8599, 2014
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Scientific journal
  ORCID：60076104, SCOPUS ID：84927613407
• ピンポイント着陸に向けた SLIM 探査機の自己位置推定とその展開　　　　　　　　　　　　　　　
  Tomohiro Harada
  宇宙科学技術連合講演会講演集, 2014
  Scientific journal
  ORCID：53313846
• 時変環境における局所的情報共有に基づく Artificial Bee Colony アルゴリズム　　　　　　　　　　　　　　　
  Tomohiro Harada
  研究報告数理モデル化と問題解決 (MPS), 2014
  Scientific journal
  ORCID：53313831
• Sleep Stage Estimation Using Synthesized Data of Heart Rate and Body Movement.
  Yusuke Tajima; Masaya Nakata; Tomohiro Harada; Keiji Sato; Keiki Takadama
  2014 AAAI Spring Symposia, Stanford University, Palo Alto, California, USA, March 24-26, 2014, 2014, [Reviewed]
  AAAI Press
  DBLP ID：conf/aaaiss/TajimaNHST14
• What is needed to promote an asynchronous program evolution in genetic programing?　　　　　　　　　　　　　　　
  Keiki Takadama; Tomohiro Harada; Hiroyuki Sato; Kiyohiko Hattori
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：8426, First page：227, Last page：241, 2014, [Reviewed]
  Unlike a synchronous program evolution in the context of evolutionary computation that evolves individuals (i.e., programs) after evaluations of all individuals in each generation, this paper focuses on an asynchronous program evolution that evolves individuals during evaluations of each individual. To tackle this problem, we explore the mechanism that can promote an asynchronous program evolution by selecting a good individual without waiting for evaluations of all individuals, and investigates its effectiveness in genetic programming (GP) domain. The intensive experiments have revealed the following implications: (1) the program asynchronously evolved with the proposed mechanism can be completed with the shorter execution steps than the program asynchronously evolved without the proposed mechanism
  and (2) the program asynchronously evolved with the proposed mechanism can be completed with mostly the same or shorter execution steps than the program synchronously evolved by the conventional GP. © 2014 Springer International Publishing.
  Springer Verlag, English, International conference proceedings
  DOI：https://doi.org/10.1007/978-3-319-09584-4_22
  DOI ID：10.1007/978-3-319-09584-4_22, ISSN：1611-3349, SCOPUS ID：84905842836
• Favor information presentation and its effect for collective-adaptive situation　　　　　　　　　　　　　　　
  Asami Mori; Tomohiro Harada; Yoshihiro Ichikawa; Keiki Takadama
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：8522, Number：2, First page：455, Last page：466, 2014, [Reviewed]
  This paper focuses onfavor information among people as the factor to lead a group to "collective-adaptive situation" and explores its effect in "Barnga" as the cross-cultural game which aims at investigating how the players make an appropriate group decision. For this purpose, we propose the "favor marker" which appears as a favor for other players in Barnga system. The subjective experiment results with this system have been revealed that the players in both the system-based communication and face-to-face communication lead the collective-adaptive situation by using the favor markers, while being conscious on the difference of card rules which caused conflicts among players. In detail, the following implications have been found: (1) when the players meet their conflict at the first time, their intentions tend to be appear from their behaviors (e.g. gesture) without using the favor maker in the face-to-face communication, while their intentions are appeared by actively using the favor marker in the system-based communication
  (2) after some conflicts, the favor marker in both types of communication showed the effect on making an aware of the difference of the card rules and facilitating behavior affected by such differences, which contributes to deriving a smooth group decision making. © 2014 Springer International Publishing.
  Springer Verlag, English, International conference proceedings
  DOI：https://doi.org/10.1007/978-3-319-07863-2_44
  DOI ID：10.1007/978-3-319-07863-2_44, ISSN：1611-3349, SCOPUS ID：84904125552
• 集団適応状態に向けた好意情報の提示とその影響　　　　　　　　　　　　　　　
  Tomohiro Harada
  電子情報通信学会論文誌 A, Volume：J97-A, Number：6, First page：429, Last page：438, 2014, [Reviewed]
  Japanese, Scientific journal
  ORCID：53313832
• 多次元空間問題における商品属性の関係理解と商品選定の支援　　　　　　　　　　　　　　　
  Tomohiro Harada
  電子情報通信学会論文誌 A, Volume：J97-A, Number：6, First page：482-491, 2014, [Reviewed]
  Japanese, Scientific journal
  ORCID：53313853
• 時変環境における局所的情報共有に基づくArtificial Bee Colonyアルゴリズム　　　　　　　　　　　　　　　
  第101回数理モデル化と問題解決研究発表会, 2014
• Multi Objective Optimization for Route Planning and Fleet Assignment in Regular and Non-regular Flights　　　　　　　　　　　　　　　
  The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014), 2014
• Artificial Bee Colony Algorithm based on Local Information Sharing in Dynamic Environment　　　　　　　　　　　　　　　
  The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES2014), 2014
• Asynchronous Evolution by Reference-based Evaluation: Tertiary Parent Selection and its Archive　　　　　　　　　　　　　　　
  17th European Conference on Genetic Programming (EuroGP2014), Lecture Notes in Computer Science, 2014
• 第三の親個体とそのアーカイブを用いたリファレンス評価による非同期進化　　　　　　　　　　　　　　　
  第6回進化計算研究会, 2014
• Maintaining, Minimizing, and Recovering Machine Language Program through SEU in On-Board Computer　　　　　　　　　　　　　　　
  International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS2014), 2014
• Asynchronously Evolving Solutions with Excessively Different Evaluation Time by Reference-based Evaluation　　　　　　　　　　　　　　　
  Genetic and Evolutionary Computation Conference 2014 (GECCO2014), 2014
• Evaluating an Integration of Spacecraft Location Estimation with Crater Detection Toward SLIM　　　　　　　　　　　　　　　
  International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS2014), 2014
• SLIM における実撮影画像のクレータ検出からの自己位置推定: クレータ誤検出にロバストな自己位置推定アルゴリズムの評価　　　　　　　　　　　　　　　
  Tomohiro Harada
  宇宙科学技術連合講演会講演集, 2013
  Scientific journal
  ORCID：53313864
• Asynchronous evaluation based genetic programming: Comparison of asynchronous and synchronous evaluation and its analysis　　　　　　　　　　　　　　　
  Tomohiro Harada; Keiki Takadama
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：7831, First page：241, Last page：252, 2013, [Reviewed]
  This paper compares an asynchronous evaluation based GP with a synchronous evaluation based GP to investigate the evolution ability of an asynchronous evaluation on the GP domain. As an asynchronous evaluation based GP, this paper focuses on Tierra-based Asynchronous GP we have proposed, which is based on a biological evolution simulator, Tierra. The intensive experiment compares TAGP with simple GP by applying them to a symbolic regression problem, and it is revealed that an asynchronous evaluation based GP has better evolution ability than a synchronous one. © 2013 Springer-Verlag.
  English, International conference proceedings
  DOI：https://doi.org/10.1007/978-3-642-37207-0_21
  DOI ID：10.1007/978-3-642-37207-0_21, ISSN：0302-9743, SCOPUS ID：84875111553
• Towards understanding of relationship among pareto optimal solutions in multi-dimensional space via interactive system　　　　　　　　　　　　　　　
  Keiki Takadama; Yuya Sawadaishi; Tomohiro Harada; Yoshihiro Ichikawa; Keiji Sato; Kiyohiko Hattori; Hiroyoki Sato; Tomohiro Yamaguchi
  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume：8018, Number：3, First page：137, Last page：146, 2013, [Reviewed]
  This paper proposes the interactive system that can help humans to understand the trade-off relationship of Pareto optimal solutions (e.g., good products from a certain aspect) in multi-dimensional space. For this purpose, the following two methods are proposed from the viewpoint of the number of evaluation criteria which should be considered by a user at one time: (i) the two fixed evaluation criteria are employed to evaluate the solutions
  and (ii) some evaluation criteria selected by a user (i.e., the number of the evaluation criteria is varied by a user) are employed to evaluate them. To investigate the effectiveness of our proposed system employing either of two methods, we conduct human subject experiments on the motor selection problem and have revealed the following implications: (i) the proposed system based on the two fixed evaluation criteria contributes to helping users to find better motors in terms of all the evaluation criteria, while (ii) the proposed system based on the selected evaluation criteria is more effective to help users to understand Pareto optimal solutions when more evaluation criteria need to be considered. © 2013 Springer-Verlag Berlin Heidelberg.
  Springer, English, International conference proceedings
  DOI：https://doi.org/10.1007/978-3-642-39226-9_16
  DOI ID：10.1007/978-3-642-39226-9_16, ISSN：0302-9743, DBLP ID：conf/hci/TakadamaSHISHSY13, SCOPUS ID：84880901595
• リファレンス評価による非同期進化：第三の親選択とそのアーカイブ　　　　　　　　　　　　　　　
  進化計算シンポジウム2013, 2013
• Analyzing Program Evolution in Genetic Programming using Asynchronous Evaluation　　　　　　　　　　　　　　　
  Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems, ECAL 2013, 2013
• Estimation of Cooperation Navigation by Multiple Rovers Using Different Positioning Technique　　　　　　　　　　　　　　　
  The 29th International Symposium on Space Technology and Science (ISTS2013), 2013
• 予測報酬に基づく個別化による学習分類子システムの学習性能の向上　　　　　　　　　　　　　　　
  中田雅也; 原田智広; 佐藤圭二; 松島裕康; 高玉圭樹
  計測自動制御学会論文集, Volume：48, Number：11, First page：713-722, Last page：722, 2012, [Reviewed]
  Japanese
  ISSN：0453-4654, CiNii Articles ID：10031128038, CiNii Books ID：AN00072392
• 非同期評価型遺伝的プログラミングによる性能向上と同期評価との比較　　　　　　　　　　　　　　　
  進化計算シンポジウム2012, 2012
• 環境変化に対応するためのスワップ型一般化　　　　　　　　　　　　　　　
  システム・情報部門学術講演会2012, 2012
• Evolving Conditional Branch Program in Tierra-based Asynchronous Genetic Programming　　　　　　　　　　　　　　　
  The 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced Intelligent Systems, 2012
• Computational Time Reduction of Evolutionary Spacecraft Location Estimation toward Smart Lander for Investigating Moon　　　　　　　　　　　　　　　
  The 11th International Symposium on Artificial Intelligence, Robotics and Automation on Space (i-SAIRAS2012), 2012
• Evolving Conditional Branch Program in Tierra-based Asynchronous Genetic Programming　　　　　　　　　　　　　　　
  The 6th International Conference on Soft Computing and Intelligent Systems, and the 13th International Symposium on Advanced Intelligent Systems (SCIS-ISIS2012), 2012
• Automatic Cartography Method by Cooperation of Autonomous Micro Robots and Its Verification Through Simulations　　　　　　　　　　　　　　　
  The International Conference on Humanized Systems 2012 (ICHS2012), 2012
• Interactive Assistant System for Understanding Pareto Solution in Multi-Dimensional Space　　　　　　　　　　　　　　　
  Triangle Symposium on Advanced ICT 2012 (TriSAI2012), 2012
• Robustness to bit inversion in registers and acceleration of program evolution in on-board computer　　　　　　　　　　　　　　　
  Tomohiro Harada; Masayuki Otani; Yoshihiro Ichikawa; Kiyohiko Hattori; Hiroyuki Sato; Keiki Takadama
  Journal of Advanced Computational Intelligence and Intelligent Informatics, Volume：15, Number：8, First page：1175, Last page：1185, 2011, [Lead, Corresponding]
  This paper focuses on an on-board computer (OBC) that evolves computer programs through bit inversion and targets analyzing robustness against bit inversion in registers. We also propose a new method that can change the number of computer programs dynamically. Intensive experiments revealed the following: (1) Correct programs can be maintained even in bit inversion in registers in addition to bit inversion in instructions. (2) Our proposal accelerates program evolution by increasing the population size, i.e., the number of programs, within fixed memory size.
  Fuji Technology Press, English, Scientific journal
  DOI：https://doi.org/10.20965/jaciii.2011.p1175
  DOI ID：10.20965/jaciii.2011.p1175, ISSN：1883-8014, SCOPUS ID：80054893841
• 個別化による学習分類子システムの一般化促進　　　　　　　　　　　　　　　
  Tomohiro Harada
  計測自動制御学会論文集, Volume：47, Number：11, First page：581-590, 2011
  Scientific journal
  ORCID：53313819
• Adaptive Mutation Depending on Program Size in Asynchronous Program Evolution　　　　　　　　　　　　　　　
  The Third World Congress on Nature and Biologically Inspired Computing (NaBIC2011), 2011
• SLIMにおける進化的三角形相似マッチングを用いた自己位置推定　　　　　　　　　　　　　　　
  第55回宇宙科学技術連合講演会, 2011
• Evolving complex programs in tierra-based on-board computer on UNITEC-1　　　　　　　　　　　　　　　
  Tomohiro Harada; Masayuki Otani; Hiroyasu Matsushima; Kiyohiko Hattori; Keiki Takadama
  61st International Astronautical Congress 2010, IAC 2010, Volume：3, First page：2203, Last page：2210, 2010
  This paper investigates the effectiveness of our proposed On-Board Computer (OBC) loaded in UNITEC-1, which is developed by the several Japanese universities and launched to Venus as the piggyback of the JAXA's satellite named "AKATSUKI" (PLANET-C) on May 21st, 2010. Unlike the conventional approaches that employ the shielded devices, the multiplex logic circuit, or CPUs with a thick process rule to protect OBC from the bit inversion (Single-Event Upset: SEU) caused by space radiation, our proposed OBC evolves the computer programs (hereafter, we just say it programs) through the bit inversion of DRAM by exposing space radiation. This is a unique approach which changes the weak point of OBC to its strong point. To develop such OBC, our previous research developed Tierra-based On-Board Computer (OBC) which employed the idea of Tierra, the biological evolution simulator, where the digital creatures (implemented by the programs) are evolved through a mutation in a gene. Since Tierra executes problems from the biological viewpoint, the following mechanisms were introduced into Tierra-based OBC to execute problems from the engineering task (e.g., orbit/attitude control, navigation task, optimization problem): (1) the fitness used in Genetic Algorithm (GA) is employed for each program to evaluate its accomplish degree
  and (2) the asynchronous GA was proposed to evaluate the programs independently (i.e., the programs are replicated when their fitness exceed a certain threshold). As the hardware architecture, Tierra-based OBC is constructed with Micro Control Unit (H8) and DRAM, and H8 evolves the programs stored in DRAM. The final goal of our mission aims at validating that Tierra-based OBC can evolve the programs through the bit inversion caused by space radiation from its experiment results downlinked from UNITEC-1. Towards this goal, this paper investigates the effectiveness of Tierra-based OBC in complex problems before launching UNITEC-1. In detail, the following experiments are conducted by artificial mutating the programs instead of the bit inversion caused by space radiation: the complexity of the program increases (1) by changing the target (output) of the problem
  (2) by changing the initial program and (3) by adding the instructions. Through the intensive experiments of Tierra-based OBC the following implications have been revealed: Tierra-based OBC maintains the correct programs and evolves the programs not depending on (1) the target of the problem and (2) the initial program
  and (3) Tierra-based OBC is also applicable to the complex programs added the instructions. Copyright ©2010 by the International Astronautical Federation. All rights reserved.
  English, International conference proceedings
  SCOPUS ID：79959406152
• Fly to Venus: Program Evolving On-Board Computer in UNITEC-1　　　　　　　　　　　　　　　
  The Third International Symposium on Robot and Artificial Intelligence, 2010
• Evaluating an Integration of Spacecraft Location Estimation with Crater Detection Toward Smart Lander for Investigating Moon　　　　　　　　　　　　　　　
  Takadama, Keiki; Harada, Tomohiro; Kamata, Hiroyuki; Ozawa, Shinji; Fukuda, Seisuke; Sawai, Syujirou
  Scientific journal
  ORCID：53313816
• Deep Features for Image Classification and Image Similarity Perception　　　　　　　　　　　　　　　
  Wei, Zhenao; Xiong, Lilang; Mori, Kazuki; Nguyen, Tung Duc; Harada, Tomohiro; Thawonmas, Ruck; Suzuki, Keiko; Kidachi, Masaaki
  JADH 2017, First page：60, Last page：60
  Scientific journal
  ORCID：53313882

• 企業参加推進　　　　　　　　　　　　　　　
  原田 智広; 吉田 諭史; 笹嶋 宗彦; 砂川 英一
  Volume：36, Number：6, First page：743, Last page：743, Dec. 2021, [Invited], [Lead]
  Japanese, Meeting report
  DOI：https://doi.org/10.11517/jjsai.36.6_742
  DOI ID：10.11517/jjsai.36.6_742
• 企業参加推進担当活動報告　　　　　　　　　　　　　　　
  米納 弘渡; 伊藤 雅弘; 原田 智広; 吉田 諭史
  Volume：35, Number：6, First page：805, Last page：805, Dec. 2020, [Invited]
  Japanese, Meeting report
  DOI：https://doi.org/10.11517/jjsai.35.6_801
  DOI ID：10.11517/jjsai.35.6_801
• Program Emergence Towards a Robust Space Computer System
  高玉 圭樹; 原田 智広
  Volume：61, First page：6p, 23 May 2017
  Japanese
  CiNii Articles ID：40021219730
• Well-being Computing : Towards Physical, Mental, and Social Well-being from Sleep Perspective　　　　　　　　　　　　　　　
  髙玉 圭樹; 村田 暁紀; 上野 史; 田島 友祐; 辰巳 嵩豊; 原田 智広
  人工知能 : 人工知能学会誌 : journal of the Japanese Society for Artificial Intelligence, Volume：32, Number：1, First page：81, Last page：86, Jan. 2017
  人工知能学会 ; 2014-, Japanese
  ISSN：2188-2266, CiNii Articles ID：40021055972, CiNii Books ID：AA12652467
• 快眠を導く音とは─ 心拍・呼吸に連動した音の睡眠への影響─　　　　　　　　　　　　　　　
  Tomohiro Harada
  人工知能, Volume：31, Number：3, 01 May 2016
  Japanese
  CiNii Articles ID：190000000150, ORCID put code：53313870
• Procedural generation of angry birds levels using building constructive grammar with chinese-style and/or japanese-style models　　　　　　　　　　　　　　　
  Jiang, YuXuan; Kaidan, Misaki; Chu, Chun Yin; Harada, Tomohiro; Thawonmas, Ruck
  arXiv preprint arXiv:1604.07906, 2016
  ORCID put code：53313842
• 非同期進化的アルゴリズムによるプログラム進化　　　　　　　　　　　　　　　
  原田 智広
  2015, [Lead, Last, Corresponding]
  Japanese
  ORCID put code：53313856
• Tierra 型非同期遺伝的アルゴリズムにおける進化の効率性向上と複雑なプログラム進化への展開　　　　　　　　　　　　　　　
  原田 智広
  Mar. 2012, [Lead]
  Japanese
  ORCID put code：53313872

• 耐故障性を備えたシステムの構築に向けた多峰性遺伝的プログラミングの提案　　　　　　　　　　　　　　　
  関係論的システム調査研究会, Jan. 2018
  Jan. 2018 - Jan. 2018
• Program Emergence Towards a Robust Space Computer System　　　　　　　　　　　　　　　
  高玉 圭樹; 原田 智広
  May 2017
  May 2017 - May 2017, Japanese
• 睡眠の質を向上する快眠音の探求　　　　　　　　　　　　　　　
  原田 智広
  Oct. 2016, [Invited]
  Japanese, Public discourse
• 非同期評価に基づく遺伝的プログラミングによる機械語プログラムの進化　　　　　　　　　　　　　　　
  第7回関係論的システム科学調査研究会, 2014
  2014 - 2014
• Tierra型オンボードコンピュータにおけるプログラム進化とその可能性　　　　　　　　　　　　　　　
  第6回関係論的システム科学調査研究会, 2013
  2013 - 2013

• Graduation Research 3, Ritsumeikan University
• Graduation Research 2, Ritsumeikan University
• Graduation Research 1, Ritsumeikan University
• Exercises in Intelligent Computing 2, Ritsumeikan University
• Graduation Research, Saitama University
• Synthetic Exercises on Information Engineering, Saitama University
• Advanced Lectures on Optimization Algorithms, Saitama University
• Computer Literacy, Saitama University
• Introductory Seminar on Engineering, Saitama University
• Applied Linear Algebra, Saitama University

• 2024

• Association for Computing Machinery (ACM)
• Institute of Electrical and Electronics Engineers (IEEE)
• The Japanese Society for Artificial Intelligence
• Information Processing Society of Japan
• The Society of Instrument and Control Engineers
• The Japanese Society for Evolutionary Computation

• 問題設定へのフィードバックで最適化プロセスを支援する進化計算　　　　　　　　　　　　　　　
  Apr. 2024 - Mar. 2028
  Principal investigator
  Grant amount(Total)：18460000, Direct funding：14200000, Indirect funding：4260000
  Grant number：24K03011
  論文ID：49476334
• Reinforcement Learning with Multi-Objective Evolutionary Computation in Strategic Decision-Making　　　　　　　　　　　　　　　
  Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Apr. 2024 - Mar. 2027
  Okayama University, Coinvestigator
  Grant amount(Total)：18460000, Direct funding：14200000, Indirect funding：4260000
  Grant number：24K03001
• 最適化ベンチマーク問題自動生成のための大規模言語モデル駆動型進化的アルゴリズム　　　　　　　　　　　　　　　
  Research Organization for Information Science and Technology, FY2025 Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures (JHPCN), Apr. 2025 - Mar. 2026
  Tomohiro Harada; Fumito Uwano; Keiki Takadama, The University of Tokyo, Principal investigator
  Grant number：jh250063
• サロゲートモデル活用による省エネルギー指向型進化計算　　　　　　　　　　　　　　　
  Mar. 2025 - Mar. 2026
  Principal investigator
  Grant number：24-05
• 二値分類機械学習モデルを用いる高コスト最適化問題に対する進化的アルゴリズム　　　　　　　　　　　　　　　
  01 Apr. 2021 - 31 Mar. 2024
  Grant amount(Total)：4680000, Direct funding：3600000, Indirect funding：1080000
  Grant number：21K17826
  論文ID：48890951, 受賞ID：36666717
• Development of functions for audience participation promotion and procedural play generation in well-being live streaming　　　　　　　　　　　　　　　
  Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Grant-in-Aid for Scientific Research (C), 01 Apr. 2019 - 31 Mar. 2022
  Thawonmas Ruck, Ritsumeikan University
  Grant amount(Total)：4290000, Direct funding：3300000, Indirect funding：990000
  This research was conducted to establish artificial intelligence methods and intellectual methods for health promotion content and verify their effectiveness on live streaming distribution platforms represented by Twitch. Specifically, we proposed algorithms that do not require any player intervention and can cope with everyday stress in the daily life of players. We have succeeded in constructing methods for generating content that promotes health and improving spectator participation that promotes social health, which shows that it is possible to maintain connections with other people and communities.
  Grant number：19K12291
• A Study of Parallel Evolutionary Algorithm Independent to Evaluation Time Variances　　　　　　　　　　　　　　　
  Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists, Grant-in-Aid for Early-Career Scientists, 01 Apr. 2019 - 31 Mar. 2021
  Harada Tomohiro, Ritsumeikan University
  Grant amount(Total)：4290000, Direct funding：3300000, Indirect funding：990000
  This research proposes an efficient parallelization method for evolutionary algorithms (PEA), which are typical methods for solving optimization problems. Conventional PEA has a problem of not obtaining the optimal solution in a short computation time when the evaluation time of solutions differs and is biased. To address this problem, this research has proposed the following three PEA approaches; (1) semi-asynchronous PEA that can arbitrarily set the asynchrony of parallelization during optimization, (2) asynchronous PEA that introduces a selection mechanism considering the search progress of solutions, and (3) synchronous PEA that improves the computer utilization rate by the precedence evaluation.
  Grant number：19K20362
  論文ID：36666767
• Reinforcing Spacecraft Computer System by Bit Inversion: Towards Sustainability Through Program Evolution　　　　　　　　　　　　　　　
  Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Grant-in-Aid for Scientific Research (B), 19 Jul. 2016 - 31 Mar. 2019
  Takadama Keiki, The University of Electro-Communications
  Grant amount(Total)：17680000, Direct funding：13600000, Indirect funding：4080000
  This project proposes the program evolution method based on bit inversion caused by space radiation in order to reinforce spacecraft computer systems against unexpected external incidents (such as sensor trouble or environmental change) and internal incidents (such as program bug). To investigate an effectiveness of the proposed method, this project focuses on the space rover and builds the design method for reinforcing the functions in the computer systems through an evaluation of the evolved programs that controls the rover.
  Grant number：16KT0103
  論文ID：21246545
• Ｔｉｅｒｒａ型オンボードコンピュータにおけるプログラム進化手法　　　　　　　　　　　　　　　
  Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for JSPS Fellows, Grant-in-Aid for JSPS Fellows, 01 Apr. 2012 - 31 Mar. 2015
  The University of Electro-Communications
  Grant amount(Total)：2700000, Direct funding：2700000
  Grant number：12J09376

• 2024 IEEE Conference on Games (CoG), Reviewer　　　　　　　　　　　　　　　
  Peer review
  2024
  Competition etc
• IEEE World Congress on Computational Intelligence 2024 (IEEE WCCI 2024), Reviewer　　　　　　　　　　　　　　　
  Peer review
  2024
  Competition etc
• ACM Genetic and Evolutionary Computation Conference 2024, Program Committee　　　　　　　　　　　　　　　
  Peer review
  2023
  Competition etc
• SICE Festival 2024 with Annual Conference, Reviewer　　　　　　　　　　　　　　　
  Peer review
  2024
  Competition etc

• 進化の力で最適化　　　　　　　　　　　　　　　
  Myself, May 2024, [Paper]