Computing a mechanism for a Bayesian and partially observable Markov approach

• Autorzy: Clempner Julio B. , Poznyak Alexander S.

Identyfikatory

DOI

10.34768/amcs-2023-0034

• Języki publikacji: EN

Abstrakty

EN

The design of incentive-compatible mechanisms for a certain class of finite Bayesian partially observable Markov games is proposed using a dynamic framework. We set forth a formal method that maintains the incomplete knowledge of both the Bayesian model and the Markov system’s states. We suggest a methodology that uses Tikhonov’s regularization technique to compute a Bayesian Nash equilibrium and the accompanying game mechanism. Our framework centers on a penalty function approach, which guarantees strong convexity of the regularized reward function and the existence of a singular solution involving equality and inequality constraints in the game. We demonstrate that the approach leads to a resolution with the smallest weighted norm. The resulting individually rational and ex post periodic incentive compatible system satisfies this requirement. We arrive at the analytical equations needed to compute the game’s mechanism and equilibrium. Finally, using a supply chain network for a profit maximization problem, we demonstrate the viability of the proposed mechanism design.

Słowa kluczowe

EN

dynamic mechanism design; partially observable Markov chains; games with private information; Bayesian equilibrium

PL

mechanizm dynamiczny; łańcuchy Markova; równowaga Bayesa

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2023
• Tom: Vol. 33, no. 3
• Strony: 463--478
• Opis fizyczny: Bibliogr. 26 poz., wykr.

Twórcy

autor

Clempner Julio B.

• School of Physics and Mathematics, National Polytechnic Institute, Av. Instituto Politécnico Nacional, Bldg. 9, San Pedro Zacatenco, Gustavo A. Madero, 07738 Mexico City, Mexico

autor

Poznyak Alexander S.

• Department of Automatic Control, Center for Research and Advanced Studies, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, 07360 Mexico City, Mexico

Bibliografia

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