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ベイジアン・ナッシュ均衡×プリンシパル・エージェント・モデル×
分野ゲーム理論ゲーム理論
系統Machine learningMachine learning
提唱年19671976
提唱者John HarsanyiMichael Jensen, William Meckling, Bengt Holmstrom
種類algorithmalgorithm
原典Harsanyi, J. C. (1967). Games with incomplete information played by Bayesian players, Parts I, II, and III. Management Science, 14(3), 159-182. 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 ↗
別名BNE, Perfect Bayesian Equilibrium, Type-Contingent EquilibriumAgency Theory, Hidden Action Problem, Moral Hazard
関連44
概要Bayesian Nash Equilibrium (BNE) extends Nash Equilibrium to games with incomplete information, where players lack full knowledge of others' payoff functions. Introduced by John Harsanyi in 1967, BNE models strategic interaction under uncertainty by representing unknown payoffs as players' private types drawn from a probability distribution. Equilibrium is found by solving for type-contingent strategies that are best responses to all possible type realizations.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.
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ScholarGate手法を比較: Bayesian Nash Equilibrium · Principal-Agent Model. 2026-06-18に以下より取得 https://scholargate.app/ja/compare