学会等発表 - 倉重 健太郎

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  1. Action selection using priority for each task -Realization of effective processing by dynamical update of priority-

    Takuya Masaki, Kentarou Kurashige,2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology,IEEE,Proceedings of 2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology,2017年09月01日,Himeji Hyogo,日本国

  2. A Study for effectiveness of Dimensionality Reduction for State-action Pair Prediction -Training set reduction using Tendency-

    Masashi Sugimoto, Naoya Iwamoto, Robert Johnston, Keizo Kanazawa, Yukinori Misaki, Kentarou Kurashige,The Third International Conference on Electronics and Software Science (ICESS2017),SDWIC,Proceedings of the Third International Conference on Electronics and Software Science,(頁 19-28),2017年08月01日,Takamatsu,日本国

  3. 経路生成形レギュレータを用いた独立二輪車両のBezier曲線経路追従

    戀塚 立太, 花島 直彦, 水上 雅人, 藤平 祥孝, 倉重 健太郎,日本機械学会ロボティクス・メカトロニクス講演会,一般社団法人 日本機械学会 ロボティクス・メカトロニクス部門,日本機械学会ロボティクス・メカトロニクス講演会予稿集,(頁 2A1-F08),2017年05月10日,福島県,日本国

  4. Application and Performance Evaluation of a Lifting Device with Alternating Rotation Hoist

    Hanchao Li, Daisuke Harada, Naohiko Hanajima, Hidekazu Kajiwara, Kentaro Kurashige, Yoshinori Fujihira, Masato Mizukami,2016 IEEE/SICE International Symposium on System Integration,IEEE/SICE,Proceedings of 2016 IEEE/SICE International Symposium on System Integration,(頁 385-390),2016年12月13日,Sapporo,日本国

  5. 周期的変化をもつ路面に於ける 状態行動対予測による姿勢安定化についての検討

    杉本 大志, 倉重 健太郎,2016年度精密工学会山口地方学術講演会,精密工学会,2016年度精密工学会山口地方学術講演会講演論文集,(頁 9-10),2016年11月26日,山口県大島郡,日本国

  6. A STUDY OF EFFECTIVENESS OF DYNAMICALLY VARYING SAMPLING RATE FOR STATE-ACTION PAIR PREDICTION

    Masashi Sugimoto, Naoya Iwamoto, Robert W. Johnston, Keizo Kanazawa, Yukinori Misaki, Kentarou Kurashige,the International Conference on Electronics and Software Science,SDIWC,Proceedings of the International Conference on Electronics and Software Science,(頁 79-87),2016年11月14日,Takamatsu,日本国

  7. IoT-aware Context Respectful Counseling Agent

    Yukiko Yamamoto, Tetsuo Shinozaki, Setsuo Tsuruta, Kentarou Kurashige, Rainer Knauf,SMC2016,IEEE,Proc. of SMC2016,(頁 4729-4736),2016年10月09日,Budapest,ハンガリー共和国

  8. Action selection using each task priority:Realization of asynchrony action selection and update priorities

    Takuya Masaki, Kentarou Kurashige,2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems,IEEE,Proceedings of 2016 Joint 8th International Conference on Soft Computing and Intelligent Systems and 2016 17th International Symposium on Advanced Intelligent Systems,(頁 908-911),2016年08月25日,Sapporo, Hokkaido,日本国

  9. A Study on the Deciding an Action Based on the Future Probabilistic Distribution

    Masashi SUGIMOTO, Kentarou KURASHIGE,The 9th International Conference on Intelligent Robotics and Applications,IEEE SMC Society,Intelligent Robotics and Applications, Proceedings, Part II, 383-394, Aug. 22-24, 2016, Tokyo, Japan, DOI:10.1007/978-3-319-43518-3, ISBN:978-3-319-43518-3, ISSN:1611-3349,(頁 383-394),2016年08月22日,Tokyo,日本国

  10. Action Learning to Single Robot Using MARL with Repeated Consultation: Realization of Repeated Consultation Interruption for the Adaptation to Environmental Change

    Yoh TAKADA, Kentarou KURASHIGE,The 9th International Conference on Intelligent Robotics and Applications,IEEE SMC Society,Intelligent Robotics and Applications, Proceedings, Part II,(頁 371-382),2016年08月22日,Tokyo,日本国

  11. Effective action selection under multi task by ignoring tasks and limiting tasks

    Takuya Masaki, Kentarou Kurashige,World Automation Congress 2016 Japanese Satellite Session,IEEE SMC Society,Proceedings of World Automation Congress 2016,(頁 1-6),2016年08月06日,Himeji,日本国

  12. Nodding Behavioral Context Respectful Counseling Agent

    Yukiko Yamamoto, Tetsuo Shinozaki, Setsuo Tsuruta, Kentarou Kurashige, Rainer Knauf,World Automation Congress 2016 Japanese Satellite Session,IEEE SMC Society,Proceedings of World Automation Congress 2016,(頁 1-6),2016年08月06日,Himeji,日本国

  13. The Proposal for Compensation to the Action of Motion Control basedon the Prediction of State-action Pair

    Masashi Sugimoto, Kentarou Kurashige,International Conference on Electronics and Software Science,SDWIC,Proceedings of the International Conference on Electronics and Software Science,(頁 35-48),2015年07月,Takamatsu,日本国

  14. ActionLearning to single robot using MAS -A proposal of Agents action decision method based repeated consultation-

    Shuhei Chiba, Kentarou Kurashige,The 10th Asian Control Conference,Asian Control Association,Proceedings of the 10th Asian Control Conference(ASCC2015),2015年05月,Kota Kinabalu,マレーシア

  15. Teaching a series of actions by the universal evaluations of each sensory information

    Kentarou Kurashige, Kaoru Nikaido,2015 IEEE Congress on Evolutionary Computation,IEEE,2015 IEEE Congress on Evolutionary Computation,(頁 2341-2346),2015年05月,Sendai,日本国

  16. The Proposal for Real-time Sequential-decision for Optimal Action using Flexible-weight Coefficient based on the State-Action Pair

    Masashi Sugimoto,KentarouKurashige,2015 IEEE Congress on Evolutionary Computation,IEEE,2015 IEEE Congress on Evolutionary Computation,(頁 544-551),2015年05月,Sendai,日本国

  17. Self-generation of reward in reinforcement learning by universal rules of interaction with the external environment

    Kentarou Kurashige, Kaoru Nikaido,2014 IEEE Symposium Series on Computational Intelligence,IEEE,2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space Proceedings,(頁 92-97),2014年12月,orlando, florida,アメリカ合衆国

  18. Real-time Sequentially Decision for Optimal Action using Prediction of the State-Action Pair

    Masashi Sugimoto, Kentarou Kurashige,2014 International Symposium on Micro-NanoMechatronics and Human Science,IEEE,Proceedings of 2014 International Symposium on Micro-NanoMechatronics and Human Science,(頁 199-204),2014年11月,Nagoya,日本国

  19. 外界とのインタラクションによる強化学習の報酬の自己生成

    二階堂芳, 倉重健太郎,第32回日本ロボット学会学術講演会,日本ロボット学会,第32回日本ロボット学会学術講演会予稿集,(頁 RSJ2014AC3J2-02),2014年09月,福岡・福岡

  20. MAS を用いた単体ロボットの行動学習-反復合議に基づくエージェントの意思決定法の提案-

    千葉秀平, 倉重健太郎,第32回日本ロボット学会学術講演会,日本ロボット学会,第32回日本ロボット学会学術講演会予稿集,(頁 RSJ2014AC3J2-01),2014年09月,福岡・福岡

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