• 496 引用
  • 10 h指数
1984 …2019

Research output per year

Pureに変更を加えた場合、すぐここに表示されます。

フィンガープリント Toshiharu Sugawaraが有効な場合、研究トピックを掘り下げます。このトピックラベルは、この人物の業績からのものです。これらはともに一意のフィンガープリントを構成します。

ネットワーク 最近の国レベルでの外部協力。点をクリックして詳細を開いてください。

研究成果

  • 496 引用
  • 10 h指数
  • 105 Conference contribution
  • 43 Article
  • 3 Chapter

Analysis of Traffic Congestion Reducer Agents on Multi-Lane Highway

Ishihara, Y. & Sugawara, T., 2019 2 1, Proceedings - 2019 2nd International Conference on Intelligent Autonomous Systems, ICoIAS 2019. Institute of Electrical and Electronics Engineers Inc., p. 135-141 7 p. 8782519. (Proceedings - 2019 2nd International Conference on Intelligent Autonomous Systems, ICoIAS 2019).

研究成果: Conference contribution

  • Cooperation and Coordination Regimes by Deep Q-Learning in Multi-agent Task Executions

    Miyashita, Y. & Sugawara, T., 2019 1 1, Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. Tetko, I. V., Karpov, P., Theis, F. & Kurková, V. (版). Springer-Verlag, p. 541-554 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 11727 LNCS).

    研究成果: Conference contribution

  • Coordinated behavior of cooperative agents using deep reinforcement learning

    Diallo, E. A. O., Sugiyama, A. & Sugawara, T., 2019 1 1, : : Neurocomputing.

    研究成果: Article

  • 3 引用 (Scopus)

    Learning of activity cycle length based on battery limitation in multi-agent continuous cooperative patrol problems

    Sugiyama, A., Wu, L. & Sugawara, T., 2019 1 1, ICAART 2019 - Proceedings of the 11th International Conference on Agents and Artificial Intelligence. Rocha, A., Steels, L. & van den Herik, J. (版). SciTePress, p. 62-71 10 p. (ICAART 2019 - Proceedings of the 11th International Conference on Agents and Artificial Intelligence; 巻数 1).

    研究成果: Conference contribution

  • Multiple world genetic algorithm to analyze individually advantageous behaviors in complex networks

    Miura, Y., Toriumi, F. & Sugawara, T., 2019 7 13, GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, p. 297-298 2 p. (GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion).

    研究成果: Conference contribution

  • 1 引用 (Scopus)