Comparer des méthodes

	Modèle d'utilité aléatoire	Équilibre de Nash
Domaine	Théorie des jeux	Théorie des jeux
Famille	Machine learning	Machine learning
Année d'origine	1974	1950
Auteur d'origine	Daniel McFadden	John Nash
Type	algorithm	algorithm
Source fondatrice	McFadden, D. (1974). Conditional logit analysis of qualitative choice behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press.	Nash, J. F. (1950). Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49.
Alias	Discrete Choice Model, Probabilistic Choice, Stochastic Utility	Lemke-Howson Equilibrium, Completely Labeled Pair
Apparentées	4	4
Résumé	The Random Utility Model explains discrete choice behavior by assuming agents derive uncertain utilities from alternatives and choose the option yielding highest utility. Introduced by Daniel McFadden in 1974, the model decomposes utility into systematic (observable) and random (idiosyncratic) components, permitting probabilistic choice predictions. The logit model, a parametric specification, yields closed-form choice probabilities that are widely used in marketing, transportation, and environmental valuation.	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.