Methoden vergleichen

	Bayesianisches Nash-Gleichgewicht	Nash-Gleichgewicht
Fachgebiet	Spieltheorie	Spieltheorie
Familie	Machine learning	Machine learning
Entstehungsjahr	1967	1950
Urheber	John Harsanyi	John Nash
Typ	algorithm	algorithm
Wegweisende Quelle	Harsanyi, J. C. (1967). Games with incomplete information played by Bayesian players, Parts I, II, and III. Management Science, 14(3), 159-182.	Nash, J. F. (1950). Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49.
Aliasnamen	BNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium	Lemke-Howson Equilibrium, Completely Labeled Pair
Verwandt	4	4
Zusammenfassung	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.	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.