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| Top Trading Cycles× | Bayesianisches Nash-Gleichgewicht× | |
|---|---|---|
| Fachgebiet | Spieltheorie | Spieltheorie |
| Familie | Machine learning | Machine learning |
| Entstehungsjahr≠ | 1974 | 1967 |
| Urheber≠ | Lloyd Shapley, Herbert Scarf | John Harsanyi |
| Typ | algorithm | algorithm |
| Wegweisende Quelle≠ | Shapley, L. S., & Scarf, H. (1974). On cores and indivisibility. Journal of Mathematical Economics, 1(1), 23-37. 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 | TTC, Shapley-Scarf Algorithm, Efficient Exchange | BNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium |
| Verwandt | 4 | 4 |
| Zusammenfassung≠ | Top Trading Cycles (TTC) is an algorithm for allocating indivisible goods to agents such that the allocation is Pareto efficient and individually rational. Developed by Lloyd Shapley and Herbert Scarf in 1974, the algorithm identifies cycles of trades in a preference digraph, executes those trades, and iteratively repeats until no further trades are beneficial. TTC is widely used in kidney exchange and housing allocation due to its efficiency and implementation simplicity. | 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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