文章基本信息
- 标题：Construction of a Learning Agent Handling Its Rewards According to Environmental Situations
- 本地全文：下载
- 作者：Koichi Moriyama ; Masayuki Numao
- 期刊名称：人工知能学会論文誌
- 印刷版ISSN：1346-0714
- 电子版ISSN：1346-8030
- 出版年度：2002
- 卷号：17
- 期号：6
- 页码：676-683
- DOI：10.1527/tjsai.17.676
- 出版社：The Japanese Society for Artificial Intelligence
- 摘要：The authors aim at constructing an agent which learns appropriate actions in a Multi-Agent environment with and without social dilemmas. For this aim, the agent must have nonrationality that makes it give up its own profit when it should do that. Since there are many studies on rational learning that brings more and more profit, it is desirable to utilize them for constructing the agent. Therefore, we use a reward-handling manner that makes internal evaluation from the agent's rewards, and then the agent learns actions by a rational learning method with the internal evaluation. If the agent has only a fixed manner, however, it does not act well in the environment with and without dilemmas. Thus, the authors equip the agent with several reward-handling manners and criteria for selecting an effective one for the environmental situation. In the case of humans, what generates the internal evaluation is usually called emotion. Hence, this study also aims at throwing light on emotional activities of humans from a constructive view.
In this paper, we divide a Multi-Agent environment into three situations and construct an agent having the reward-handling manners and the criteria. We observe that the agent acts well in all the three Multi-Agent situations composed of homogeneous agents.
- 关键词：reinforcement learning ; reward handling ; multi-agents ; social dilemma ; tragedy of the commons ; emotion
