確率的傾斜法とメモリベース的な手法を組み合わせた強化学習法

DOI Web Site Web Site 参考文献19件

書誌事項

タイトル別名
  • A Reinforcement Learning Using a Stochastic Gradient Method with Memory-Based Learning
  • カクリツテキ ケイシャホウ ト メモリベーステキナ シュホウ オ クミアワセタ キョウカ ガクシュウホウ

この論文をさがす

抄録

In this paper, for agents working on POMDP, a learning algorithm combining the memory-less learning and the memory-based learning is proposed. At first stage of the propposed algorithm, memory-less learning is applied. As a memory-less learning algorithm, the stochastic gradient method is employed. While the first stage, a state-action set series that accmplish the task is stored in memory. In the second stage, the memory-based learning is applied. In this process, only the series that obtained the first stage is used, so that this method is able to reduce the number of required memory effectively.<br>The proposed algorithm are applied three kinds of simulation to be compared with memory-less learning algorithm. Through the computer simulations, it shown that the proposed algorithms works effectively in POMDP than ordinary memory-less learnings.

収録刊行物

参考文献 (19)*注記

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