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Evolutsiooniline mänguteooria×Bayesi Nash-tasakaal×
ValdkondMänguteooriaMänguteooria
PerekondMachine learningMachine learning
Tekkeaasta19731967
LoojaJohn Maynard Smith, George PriceJohn Harsanyi
Tüüpalgorithmalgorithm
AlgallikasSmith, J. M., & Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427), 15-18. DOI ↗Harsanyi, J. C. (1967). Games with incomplete information played by Bayesian players, Parts I, II, and III. Management Science, 14(3), 159-182. DOI ↗
RööpnimetusedESS, Evolutionarily Stable Strategy, Replicator DynamicsBNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium
Seotud44
KokkuvõteEvolutionary Game Theory applies game-theoretic reasoning to biological evolution and social dynamics, where populations of agents with different strategies interact repeatedly. Introduced by John Maynard Smith and George Price in 1973, the framework uses the concept of Evolutionarily Stable Strategies (ESS) to identify strategy distributions that cannot be invaded by mutant strategies. Replicator dynamics describe how strategy frequencies evolve over time when reproduction is proportional to payoff success.Bayesian Nash Equilibrium (BNE) extends Nash Equilibrium to games with incomplete information, where players lack full knowledge of others' payoff functions. Introduced by John Harsanyi in 1967, BNE models strategic interaction under uncertainty by representing unknown payoffs as players' private types drawn from a probability distribution. Equilibrium is found by solving for type-contingent strategies that are best responses to all possible type realizations.
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ScholarGateVõrdle meetodeid: Evolutionary Game Theory · Bayesian Nash Equilibrium. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare