Methoden vergleichen

	Modell der Zufallsnutzung (Random Utility Model)	Nash-Gleichgewicht
Fachgebiet	Spieltheorie	Spieltheorie
Familie	Machine learning	Machine learning
Entstehungsjahr	1974	1950
Urheber	Daniel McFadden	John Nash
Typ	algorithm	algorithm
Wegweisende Quelle	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.
Aliasnamen	Discrete Choice Model, Probabilistic Choice, Stochastic Utility	Lemke-Howson Equilibrium, Completely Labeled Pair
Verwandt	4	4
Zusammenfassung	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.