Replicator Dynamics for Multi-agent Learning An Orthogonal Approach Michael Kaisers Maastricht University, P.O. Box 616, 6200 MD Maastricht August 28, 2009 Abstract - Replicator - Document - PDFSEARCH.IO

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	Replicator Dynamics for Multi-agent Learning An Orthogonal Approach Michael Kaisers Maastricht University, P.O. Box 616, 6200 MD Maastricht August 28, 2009 Abstract Add to Reading List Document Date: 2012-04-29 08:02:00 Open Document File Size: 660,37 KB Share Result on Facebook Company Multi-Agent Systems / Cambridge University Press / MIT Press / Dynamical Systems / / Facility Multi-agent Learning An Orthogonal Approach Michael Kaisers Maastricht University / University Press / / IndustryTerm heuristic search / find solutions / learning algorithm / real life applications / learning algorithms / energy / / Organization Cambridge University / Organisation for Scientific Research / Multi-agent Learning An Orthogonal Approach Michael Kaisers Maastricht University / MIT / / Person Morris W. Hirsch / Robert B. Leighton / Karl Sigmund / Matthew Sands / Josef Hofbauer / Addison Wesley / Richard P. Feynman / Stephen Smale / Robert Devaney / / Position actor / player / second player / / PublishedMedium Journal of Economic Theory / / Technology learning algorithm / Cross Learning algorithm / One protocol / simulation / Q-learning algorithm / / SocialTag Evolutionary dynamics Science Replicator equation Reinforcement learning Dynamics Learning automata Evolutionarily stable strategy Dynamical system Q-learning Game theory

Replicator Dynamics for Multi-agent Learning An Orthogonal Approach Michael Kaisers Maastricht University, P.O. Box 616, 6200 MD Maastricht August 28, 2009 AbstractAdd to Reading List