Determining the Optimal Strategies for Antagonistic Positional Games in Markov Decision Processes

Dmitrii Lozovanu () and Stefan Pickl ()
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Dmitrii Lozovanu: Academy of Sciences of Moldova
Stefan Pickl: Universität der Bundeswehr München

A chapter in Operations Research Proceedings 2011, 2012, pp 229-234 from Springer

Abstract: Abstract A class of stochastic antagonistic positional games for Markov decision processes with average and expected total discounted costs’ optimization criteria are formulated and studied. Saddle point conditions in the considered class of games that extend saddle point conditions for deterministic parity games are derived. Furthermore, algorithms for determining the optimal stationary strategies of the players are proposed and grounded.

Keywords: Nash Equilibrium; Payoff Function; Markov Decision Process; Stationary Strategy; Markov Decision Problem (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-642-29210-1_37

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DOI: 10.1007/978-3-642-29210-1_37

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