Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems

DOI10.1007/978-3-319-65479-9zbMath1415.91002OpenAlexW2735346538MaRDI QIDQ4978559

Tatiana Tatarenko

Publication date: 25 August 2017

Full work available at URL: https://doi.org/10.1007/978-3-319-65479-9

zbMATH Keywords

optimizationmulti-agent systemlogit dynamicsstochastic methodgame-theoretic learningmemoryless learning algorithm

Mathematics Subject Classification ID

Research exposition (monographs, survey articles) pertaining to game theory, economics, and finance (91-02) Other game-theoretic models (91A40) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Rationality and learning in game theory (91A26)

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