Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Value Shapley× | Равновесие Нэша× | |
|---|---|---|
| Область | Теория игр | Теория игр |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 1953 | 1950 |
| Автор метода≠ | Lloyd Shapley | John Nash |
| Тип | algorithm | algorithm |
| Основополагающий источник≠ | Shapley, L. S. (1953). A value for n-person games. In H. W. Kuhn & A. W. Tucker (Eds.), Contributions to the Theory of Games II (pp. 307-317). Princeton University Press. DOI ↗ | Nash, J. F. (1950). Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49. DOI ↗ |
| Другие названия≠ | Fair Division, Cooperative Game Solution, Dividend Vector | Lemke-Howson Equilibrium, Completely Labeled Pair |
| Связанные | 4 | 4 |
| Сводка≠ | The Shapley Value is a solution concept for coalition games that distributes total payoff fairly among players based on their marginal contributions to coalitions. Introduced by Lloyd Shapley in 1953, the Shapley Value is the unique payoff distribution that satisfies four intuitive axioms: efficiency (total payoff is distributed), symmetry (identical players receive equal payoff), null player (players contributing nothing receive nothing), and additivity across games. | 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. |
| ScholarGateНабор данных ↗ |
|
|