Markov Games with Frequent Actions and Incomplete Information

Pierre Cardaliaguet (), Catherine Rainer (), Dinah Rosenberg and Nicolas Vieille ()

No 1007, HEC Research Papers Series from HEC Paris

Abstract: We study a two-player, zero-sum, stochastic game with incomplete information on one side in which the players are allowed to play more and more frequently. The informed player observes the realization of a Markov chain on which the payoffs depend, while the non-informed player only observes his opponent's actions. We show the existence of a limit value as the time span between two consecutive stages vanishes; this value is characterized through an auxiliary optimization problem and as the solution of an Hamilton-Jacobi equation.

Keywords: stochastic; zero sum; Markov chain; Hamilton-Jacobi equation; incomplete information (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2013-10-24
New Economics Papers: this item is included in nep-cta, nep-gth, nep-hpe, nep-mic and nep-ore
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:ebg:heccah:1007

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