Computing a mechanism for a Bayesian and partially observable Markov approach - Clempner, Julio B.; Poznyak, Alexander S. (Zielona Góra: Uniwersytet Zielonogórski)
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.
Keywords: dynamic mechanism design; partially observable Markov chains; games with private information; Bayesian equilibrium; regularization