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Constrained Markov Decision Chains

Author

Listed:
  • Cyrus Derman

    (Columbia University)

  • Arthur F. Veinott, Jr.

    (Stanford University)

Abstract

We consider finite state and action discrete time parameter Markov decision chains. The objective is to provide an algorithm for finding a policy that minimizes the long-run expected average cost when there are linear side conditions on the limit points of the expected state-action frequencies. This problem has been solved previously only for the case where every deterministic stationary policy has at most one ergodic class. This note removes that restriction by applying the Dantzig-Wolfe decomposition principle.

Suggested Citation

  • Cyrus Derman & Arthur F. Veinott, Jr., 1972. "Constrained Markov Decision Chains," Management Science, INFORMS, vol. 19(4-Part-1), pages 389-390, December.
  • Handle: RePEc:inm:ormnsc:v:19:y:1972:i:4-part-1:p:389-390
    DOI: 10.1287/mnsc.19.4.389
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    Cited by:

    1. Michael Katehakis & Ingram Olkin & Sheldon Ross & Jian Yang, 2013. "On the life and work of Cyrus Derman," Annals of Operations Research, Springer, vol. 208(1), pages 5-26, September.
    2. Nielsen, Lars Relund & Kristensen, Anders Ringgaard, 2006. "Finding the K best policies in a finite-horizon Markov decision process," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1164-1179, December.

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