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Finite-Memory Suboptimal Design for Partially Observed Markov Decision Processes

Author

Listed:
  • Chelsea C. White

    (University of Michigan, Ann Arbor, Michigan)

  • William T. Scherer

    (University of Virginia, Charlottesville, Virginia)

Abstract

We develop bounds on the value function and a suboptimal design for the partially observed Markov decision process. These bounds and suboptimal design are based on the M most recent observations and actions. An a priori measure of the quality of these bounds is given. We show that larger M implies tighter bounds. An operations count analysis indicates that ( # A # Z ) M +1 ( # S ) multiplications and additions are required per successive approximations iteration of the suboptimal design algorithm, where A , Z , and S are the action, observation, and state spaces, respectively, suggesting the algorithm is of potential use for problems with large state spaces. A preliminary numerical study indicates that the quality of the suboptimal design can be excellent.

Suggested Citation

  • Chelsea C. White & William T. Scherer, 1994. "Finite-Memory Suboptimal Design for Partially Observed Markov Decision Processes," Operations Research, INFORMS, vol. 42(3), pages 439-455, June.
    • Handle: RePEc:inm:oropre:v:42:y:1994:i:3:p:439-455
    DOI: 10.1287/opre.42.3.439
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    Cited by:

    1. James T. Treharne & Charles R. Sox, 2002. "Adaptive Inventory Control for Nonstationary Demand and Partial Information," Management Science, INFORMS, vol. 48(5), pages 607-624, May.
    2. Yanling Chang & Alan Erera & Chelsea White, 2015. "Value of information for a leader–follower partially observed Markov game," Annals of Operations Research, Springer, vol. 235(1), pages 129-153, December.
    3. Yasemin Serin & Zeynep Muge Avsar, 1997. "Markov decision processes with restricted observations: Finite horizon case," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(5), pages 439-456, August.
    4. Hao Zhang, 2010. "Partially Observable Markov Decision Processes: A Geometric Technique and Analysis," Operations Research, INFORMS, vol. 58(1), pages 214-228, February.
    5. Yanling Chang & Alan Erera & Chelsea White, 2015. "A leader–follower partially observed, multiobjective Markov game," Annals of Operations Research, Springer, vol. 235(1), pages 103-128, December.

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