Modelling the Dynamics of Regret Minimization in Large Agent Populations: a Master Equation Approach

Zhen Wang, Chunjiang Mu, Shuyue Hu, Chen Chu, Xuelong Li

科研成果: 书/报告/会议事项章节会议稿件同行评审

145 引用 (Scopus)

摘要

Understanding the learning dynamics in multiagent systems is an important and challenging task. Past research on multi-agent learning mostly focuses on two-agent settings. In this paper, we consider the scenario in which a population of infinitely many agents apply regret minimization in repeated symmetric games. We propose a new formal model based on the master equation approach in statistical physics to describe the evolutionary dynamics in the agent population. Our model takes the form of a partial differential equation, which describes how the probability distribution of regret evolves over time. Through experiments, we show that our theoretical results are consistent with the agent-based simulation results.

源语言英语
主期刊名Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
编辑Luc De Raedt, Luc De Raedt
出版商International Joint Conferences on Artificial Intelligence
534-540
页数7
ISBN(电子版)9781956792003
DOI
出版状态已出版 - 2022
活动31st International Joint Conference on Artificial Intelligence, IJCAI 2022 - Vienna, 奥地利
期限: 23 7月 202229 7月 2022

出版系列

姓名IJCAI International Joint Conference on Artificial Intelligence
ISSN(印刷版)1045-0823

会议

会议31st International Joint Conference on Artificial Intelligence, IJCAI 2022
国家/地区奥地利
Vienna
时期23/07/2229/07/22

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