電気学会論文誌C(電子・情報・システム部門誌)
Online ISSN : 1348-8155
Print ISSN : 0385-4221
ISSN-L : 0385-4221
<ソフトコンピューティング・学習>
汎化能力を有する強化学習による最適経路問題の解法
飯間 等大西 鴻哉
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ジャーナル 認証あり

2019 年 139 巻 12 号 p. 1494-1500

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In applying reinforcement learning to a different environment, relearning is generally required. The relearning, however, is time-consuming, and therefore a method without the relearning should be developed. This paper proposes a reinforcement learning method with generalization ability for solving an optimal routing problem with a given set of multiple goal positions. The proposed method can rapidly find the optimal route for any set of the multiple goal positions once a reinforcement learning agent learns. In the proposed method, a graph search algorithm determines the visiting order of the goal positions, and an ordinary learning algorithm such as Q-learning determines each route between goal positions. The performance of the proposed method is evaluated through numerical experiments.

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