Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Алгоритм Топ-Трейдинг Циклов× | Модель «принципал-агент»× | |
|---|---|---|
| Область | Теория игр | Теория игр |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 1974 | 1976 |
| Автор метода≠ | Lloyd Shapley, Herbert Scarf | Michael Jensen, William Meckling, Bengt Holmstrom |
| Тип | algorithm | algorithm |
| Основополагающий источник≠ | Shapley, L. S., & Scarf, H. (1974). On cores and indivisibility. Journal of Mathematical Economics, 1(1), 23-37. 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 ↗ |
| Другие названия | TTC, Shapley-Scarf Algorithm, Efficient Exchange | Agency Theory, Hidden Action Problem, Moral Hazard |
| Связанные | 4 | 4 |
| Сводка≠ | 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. | 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. |
| ScholarGateНабор данных ↗ |
|
|