A Markovian Stackelberg game approach for computing an optimal dynamic mechanism

DOI10.1007/s40314-021-01578-4zbMath1476.91030OpenAlexW3178574358MaRDI QIDQ2245712

Julio B. Clempner

Publication date: 15 November 2021

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40314-021-01578-4

zbMATH Keywords

Bayesian equilibriumdynamic mechanism designMarkov gamesincentive-compatible mechanismsStackelberg games with private information

Mathematics Subject Classification ID

Bayesian problems; characterization of Bayes procedures (62C10) Noncooperative games (91A10) Hierarchical games (including Stackelberg games) (91A65) Numerical analysis or methods applied to Markov chains (65C40) Stochastic learning and adaptive control (93E35) Rationality and learning in game theory (91A26) Signaling and communication in game theory (91A28)

Related Items (2)

Learning Machiavellian strategies for manipulation in Stackelberg security games ⋮ A Bayesian reinforcement learning approach in Markov games for computing near-optimal policies

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