Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Algoritmo de Gale-Shapley× | Equilibrio de Nash Bayesiano× | |
|---|---|---|
| Campo | Teoría de juegos | Teoría de juegos |
| Familia | Machine learning | Machine learning |
| Año de origen≠ | 1962 | 1967 |
| Autor original≠ | David Gale, Lloyd Shapley | John Harsanyi |
| Tipo | algorithm | algorithm |
| Fuente seminal≠ | Gale, D., & Shapley, L. S. (1962). College admissions and the stability of marriage. The American Mathematical Monthly, 69(1), 9-15. 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 ↗ |
| Alias | Stable Marriage Problem, Deferred Acceptance, Two-Sided Matching | BNE, Perfect Bayesian Equilibrium, Type-Contingent Equilibrium |
| Relacionados | 4 | 4 |
| Resumen≠ | The Gale-Shapley algorithm solves the stable marriage problem: how to match two groups (e.g., medical residents to hospitals, students to schools) such that no pair prefers each other to their assigned partners. Introduced by David Gale and Lloyd Shapley in 1962, the algorithm guarantees a stable matching in polynomial time through a deferred acceptance process where one side proposes sequentially and the other side responds, revising choices as better options arrive. | 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. |
| ScholarGateConjunto de datos ↗ |
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