Abstract
Standard game theory relies on the assumption that players are rational agents that try to maximize their payoff. Experiments with human players indicate that Nash equilibrium is seldom played. The goal of proposed approach is to explore more nuance equilibria by allowing a player to be biased towards different equilibria in a fuzzy manner. Several classes of equilibria (Nash, Pareto, Nash-Pareto) are defined by using appropriate generative relations. An evolutionary technique for detecting fuzzy equilibria is considered. Experimental results on Cournot’ duopoly game illustrate evolutionary detection of proposed fuzzy equilibria.
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Dumitrescu, D., Lung, R.I., Mihoc, T.D., Nagy, R. (2010). Fuzzy Nash-Pareto Equilibrium: Concepts and Evolutionary Detection. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6024. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12239-2_8
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DOI: https://doi.org/10.1007/978-3-642-12239-2_8
Publisher Name: Springer, Berlin, Heidelberg
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