Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Значення Шеплі× | Модель «Принципал-Агент»× | |
|---|---|---|
| Галузь | Теорія ігор | Теорія ігор |
| Родина | Machine learning | Machine learning |
| Рік появи≠ | 1953 | 1976 |
| Автор методу≠ | Lloyd Shapley | Michael Jensen, William Meckling, Bengt Holmstrom |
| Тип | algorithm | algorithm |
| Основоположне джерело≠ | 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 ↗ | Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3(4), 305-360. DOI ↗ |
| Інші назви | Fair Division, Cooperative Game Solution, Dividend Vector | Agency Theory, Hidden Action Problem, Moral Hazard |
| Пов'язані | 4 | 4 |
| Підсумок≠ | 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. | The Principal-Agent Model analyzes how a principal (e.g., owner, employer, policymaker) can incentivize an agent (e.g., manager, employee, firm) to act in the principal's interest when the agent has private information or can take hidden actions. Formalized by Jensen and Meckling in 1976, the model identifies agency costs arising from moral hazard (the agent exerts less effort than desired) and adverse selection (the agent hides unfavorable information). Optimal contracts balance incentives with risk allocation. |
| ScholarGateНабір даних ↗ |
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