{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T16:30:13Z","timestamp":1779381013645,"version":"3.53.1"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.24963\/ijcai.2022\/76","type":"proceedings-article","created":{"date-parts":[[2022,7,15]],"date-time":"2022-07-15T22:55:56Z","timestamp":1657925756000},"page":"534-540","source":"Crossref","is-referenced-by-count":147,"title":["Modelling the Dynamics of Regret Minimization in Large Agent Populations: a Master Equation Approach"],"prefix":"10.24963","author":[{"given":"Zhen","family":"Wang","sequence":"first","affiliation":[{"name":"School of Cybersecurity, Northwestern Polytechnical University"},{"name":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunjiang","family":"Mu","sequence":"additional","affiliation":[{"name":"School of Cybersecurity, Northwestern Polytechnical University"},{"name":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuyue","family":"Hu","sequence":"additional","affiliation":[{"name":"Shanghai Artificial Intelligence Laboratory"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Chu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University"},{"name":"School of Statistics and Mathematics, Yunnan University of Finance and Economics"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuelong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}","theme":"Artificial Intelligence","location":"Vienna, Austria","acronym":"IJCAI-2022","number":"31","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2022,7,23]]},"end":{"date-parts":[[2022,7,29]]}},"container-title":["Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T07:07:34Z","timestamp":1658128054000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2022\/76"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2022,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2022\/76","relation":{},"subject":[],"published":{"date-parts":[[2022,7]]}}}