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No 1007:
Markov Games with Frequent Actions and Incomplete Information

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

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; (follow links to similar papers)

JEL-Codes: C00; (follow links to similar papers)

37 pages, October 24, 2013

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