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The Evolution of Fuzzy Rules as Strategies in Two‐Player Games
Author(s) -
West James E.,
Linster Bruce
Publication year - 2003
Publication title -
southern economic journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.762
H-Index - 58
eISSN - 2325-8012
pISSN - 0038-4038
DOI - 10.1002/j.2325-8012.2003.tb00522.x
Subject(s) - nash equilibrium , mathematical economics , simple (philosophy) , cournot competition , repeated game , fuzzy logic , best response , symmetric game , solution concept , computer science , normal form game , game theory , mathematical optimization , mathematics , artificial intelligence , philosophy , epistemology
This paper describes simulations using fuzzy rules that show how Nash equilibrium behavior can be achieved by boundedly rational agents in two‐player games with infinite strategy spaces. That is, we show how agents using simple “rules of thumb” can achieve near‐equilibrium outcomes without any overt computation of the equilibrium. This is accomplished by using a genetic algorithm to approximate repeated play. Two games of differing complexities, both with analytic solutions, are examined: a repeated linear‐demand Cournot game and a contestable rent game. When fuzzy rules used only the most recent information, the games we examined converged to outcomes similar to their respective Coumot‐Nash equilibrium outcomes. When fuzzy rules “remembered” play from the more distant past, we found that the games converged more slowly, if at all.