経路探索問題に対して深層学習との併用により汎化能力を向上させた強化学習法

DOI Web Site Web Site 参考文献8件
  • 飯間 等
    京都工芸繊維大学情報工学・人間科学系
  • 大西 鴻哉
    京都工芸繊維大学情報工学・人間科学系

書誌事項

タイトル別名
  • Reinforcement Learning Method with Generalization Ability Developed by Using Deep Learning for Solving a Path Finding Problem
  • ケイロ タンサク モンダイ ニ タイシテ シンソウ ガクシュウ ト ノ ヘイヨウ ニ ヨリ ハンカ ノウリョク オ コウジョウ サセタ キョウカ ガクシュウホウ

この論文をさがす

抄録

<p>Nowadays, deep learning and reinforcement learning have given high performance in various fields, and attracted much attention. In order to apply these learning methods to real problems, they must have a sufficient generalization ability. Whereas to improve the generalization ability has been actively studied in some fields such as image recognition and speech recognition, it has not been sufficiently studied for sequential decision-making problems such as game play and path finding. This paper proposes a reinforcement learning method with the generalization ability developed by using deep learning for a path finding problem, which is one of the sequential decision-making problems. Experimental results show that the generalization ability of the proposed method is superior to that of deep learning methods and deep reinforcement learning methods.</p>

収録刊行物

参考文献 (8)*注記

もっと見る

関連プロジェクト

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ