Comparer des méthodes

	Théorie des jeux évolutionnistes	Équilibre de Nash
Domaine	Théorie des jeux	Théorie des jeux
Famille	Machine learning	Machine learning
Année d'origine	1973	1950
Auteur d'origine	John Maynard Smith, George Price	John Nash
Type	algorithm	algorithm
Source fondatrice	Smith, J. M., & Price, G. R. (1973). The logic of animal conflict. Nature, 246(5427), 15-18.	Nash, J. F. (1950). Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49.
Alias	ESS, Evolutionarily Stable Strategy, Replicator Dynamics	Lemke-Howson Equilibrium, Completely Labeled Pair
Apparentées	4	4
Résumé	Evolutionary 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.	Nash Equilibrium is a game-theoretic solution concept where no player can unilaterally deviate to improve their payoff. Formalized by John Nash in 1950, the Lemke-Howson algorithm computationally finds equilibria in bimatrix games by identifying completely labeled vertex pairs in the strategy polytopes.