Empirical Evaluation of an Average Reward Learning Method Handling Simultaneous Learning Episodes in a Dynamic Environment with Emerging Tasks
- Resource Type
- Journal Article
- Authors
- Alex Valdivielso; Toshiyuki Miyamoto; ヴァルディヴィエルソ アレックス; 宮本 俊幸
- Source
- Proceedings of the Annual Conference of the Institute of Systems, Control and Information Engineers. 2010, :259
- Subject
- Average Reward
Dynamic Environment
Learning Episode
Reinforcement Learning
動的環境
学習エピソード
平均報酬
強化学習
- Language
- Japanese
Average learning methods (ARLMs) show a poor performance in environments in which they must deal with several tasks simultaneously. In this paper we present the evaluation of an ARLM adapted to handle simultaneous learning episodes. We compare its performance against a conventional ARLM in a multicar elevator system.