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| Gleichgewicht nach Arrow-Debreu× | Bayesianisches Nash-Gleichgewicht× | |
|---|---|---|
| Fachgebiet | Spieltheorie | Spieltheorie |
| Familie | Machine learning | Machine learning |
| Entstehungsjahr≠ | 1954 | 1967 |
| Urheber≠ | Kenneth Arrow, Gerard Debreu | John Harsanyi |
| Typ | algorithm | algorithm |
| Wegweisende Quelle≠ | Arrow, K. J., & Debreu, G. (1954). Existence of an equilibrium for competitive economies. Econometrica, 22(3), 265-290. DOI ↗ | Harsanyi, J. C. (1967). Games with incomplete information played by Bayesian players, Parts I, II, and III. Management Science, 14(3), 159-182. DOI ↗ |
| Aliasnamen | Walrasian Equilibrium, General Equilibrium, Competitive Equilibrium | BNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | The Arrow-Debreu model is a general equilibrium framework where prices adjust to clear all markets simultaneously, and consumers and firms optimize given those prices. Introduced by Kenneth Arrow and Gerard Debreu in 1954, the model extends Adam Smith's invisible hand concept into a rigorous mathematical framework. Arrow-Debreu equilibrium proves existence, uniqueness (under certain conditions), and Pareto efficiency of competitive equilibria. | 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. |
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