Partially Observable Discrete-time Discounted Markov Games with General Utility

2022/11/15 by Arnab Bhabak, Bhabak, Arnab, Subhamay Saha +1 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · #Economic theories and models #FOS: Mathematics #Game Theory and Applications #Optimization and Control (math.OC)

paper · pdf · doi:10.48550/arxiv.2211.07888

openalex publication_date 2022/11/15 · openalex created_date 2022/11/24 · openalex updated_date 2026/07/28

Abstract

In this paper, we investigate a partially observable zero sum games where the state process is a discrete time Markov chain. We consider a general utility function in the optimization criterion. We show the existence of value for both finite and infinite horizon games and also establish the existence of optimal polices. The main step involves converting the partially observable game into a completely observable game which also keeps track of the total discounted accumulated reward/cost.

Cited by

• Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria

Related

• Zero-Sum Stochastic Games with Partial Information and Average Payoff
• Finite-Horizon Partially Observable Semi-Markov Games with Risk Probability Criteria
• Discrete-time Zero-Sum Games for Markov chains with risk-sensitive average cost criterion
• Zero-Sum Games for piecewise deterministic Markov decision processes with risk-sensitive finite-horizon cost criterion
• Zero-sum continuous-time Markov pure jump game over a fixed duration