ScholarGate
Asystent

Porównaj metody

Przeglądaj wybrane metody obok siebie; wiersze, które się różnią, są wyróżnione.

Model główny-agent×Równowaga Nasha×
DziedzinaTeoria gierTeoria gier
RodzinaMachine learningMachine learning
Rok powstania19761950
TwórcaMichael Jensen, William Meckling, Bengt HolmstromJohn Nash
Typalgorithmalgorithm
Źródło pierwotneJensen, 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 ↗Nash, J. F. (1950). Equilibrium points in N-person games. Proceedings of the National Academy of Sciences, 36(1), 48-49. DOI ↗
Inne nazwyAgency Theory, Hidden Action Problem, Moral HazardLemke-Howson Equilibrium, Completely Labeled Pair
Pokrewne44
PodsumowanieThe 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.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.
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

Przejdź do wyszukiwania Pobierz slajdy

ScholarGatePorównaj metody: Principal-Agent Model · Nash Equilibrium. Pobrano 2026-06-18 z https://scholargate.app/pl/compare