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	Equilibrio di Nash Bayesiano	Equilibrio di Nash
Campo	Teoria dei giochi	Teoria dei giochi
Famiglia	Machine learning	Machine learning
Anno di origine	1967	1950
Ideatore	John Harsanyi	John Nash
Tipo	algorithm	algorithm
Fonte seminale	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.
Alias	BNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium	Lemke-Howson Equilibrium, Completely Labeled Pair
Correlati	4	4
Sintesi	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.