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A policy-improvement type algorithm for solving zero-sum two-person stochastic games of perfect information

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Abstract.

 We give a policy-improvement type algorithm to locate an optimal pure stationary strategy for discounted stochastic games with perfect information. A graph theoretic motivation for our algorithm is presented as well.

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Authors and Affiliations

  1. Department of Mathematics, Statistics and Computer Science, University of Illinois at Chicago, e-mail: ter@uic.edu, , , , , , US

    T.E.S. Raghavan

  2. The Hull Group L.L.C, Chicago, IL 60606, e-mail: zsyed@hdc.com, , , , , , US

    Zamir Syed

Authors
  1. T.E.S. Raghavan
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  2. Zamir Syed
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Additional information

Received: January 1998 / Accepted: May 2002 Published online: February 14, 2003

Key words. stochastic games – MDP – perfect information – policy iteration

Partially Funded by NSF Grant DMS 930-1052 and DMS 970-4951

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Raghavan, T., Syed, Z. A policy-improvement type algorithm for solving zero-sum two-person stochastic games of perfect information. Math. Program., Ser. A 95, 513–532 (2003). https://doi.org/10.1007/s10107-002-0312-3

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  • DOI: https://doi.org/10.1007/s10107-002-0312-3

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