Salīdzināt metodes

	Modelis "Principāls-Aģents"	Šepli vērtība
Nozare	Spēļu teorija	Spēļu teorija
Saime	Machine learning	Machine learning
Izcelsmes gads	1976	1953
Autors	Michael Jensen, William Meckling, Bengt Holmstrom	Lloyd Shapley
Tips	algorithm	algorithm
Pirmavots	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.	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.
Citi nosaukumi	Agency Theory, Hidden Action Problem, Moral Hazard	Fair Division, Cooperative Game Solution, Dividend Vector
Saistītās	4	4
Kopsavilkums	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.	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.