Multi-Agent Reinforcement Learning and Genetic Policy Sharing

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dc.creatorEllowitz, Jake
dc.date2008-12-09
dc.date.accessioned2026-07-07T12:10:44Z
dc.date.available2026-07-07T12:10:44Z
dc.descriptionThe effects of policy sharing between agents in a multi-agent dynamical system has not been studied extensively. I simulate a system of agents optimizing the same task using reinforcement learning, to study the effects of different population densities and policy sharing. I demonstrate that sharing policies decreases the time to reach asymptotic behavior, and results in improved asymptotic behavior.
dc.description7 pages, 11 figures
dc.identifierhttps://arxiv.org/abs/0812.1599
dc.identifierhttp://arxiv.org/abs/0812.1599
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/210017
dc.subjectMultiagent Systems
dc.subjectArtificial Intelligence
dc.titleMulti-Agent Reinforcement Learning and Genetic Policy Sharing
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