NDLI: Empirical evidence equilibria in stochastic games

Content Provider	IEEE Xplore Digital Library
Author	Dudebout, N. Shamma, J.S.
Copyright Year	2012
Description	Author affiliation: Decision and Control Laboratory, Georgia Institute of Technology, Atlanta, 30332 USA (Dudebout, N.; Shamma, J.S.)
Abstract	The framework of empirical evidence equilibrium (EEE) for stochastic games is developed in this paper. In a stochastic game, agents collectively influence the dynamic of the environment. In standard equilibria, each agent's strategy is optimal with respect to its opponents' strategies. Therefore, each strategy is the solution to a partially observable Markov decision process (POMDP). The following considerations motivate the notion of EEE. First, solutions to a POMDP can be prohibitively complex to compute and implement. Second, agents might not fully understand the environment's dynamic. Third, standard equilibria do not accommodate different levels of bounded rationality among agents. Finally, reaching equilibrium in stochastic games has not been adequately addressed. In the EEE framework, each agent formulates a simple model of its opponents' effects. It neglects that agents are mutually dependent through the environment and computes an optimal strategy associated with its model. The agents play their strategies against each other and make some observations. Agents are in EEE when the models are consistent with these empirical observations. In this paper, the notion of EEE is formalized and an existence result is established in a general setting. Relations with other equilibria, including mean field equilibria, are also presented. Finally, the learning of EEEs by simple adaptive processes is illustrated through simulation.
Starting Page	5780
Ending Page	5785
File Size	315990
Page Count	6
File Format	PDF
ISBN	9781467320658
ISSN	07431546
e-ISBN	9781467320665
e-ISBN	9781467320641
DOI	10.1109/CDC.2012.6426118
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Games Computational modeling Markov processes History Monitoring Face
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

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