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Computation of weighted sums of rewards for concurrent MDPs

Author

Listed:
  • Peter Buchholz

    (Informatik IV, TU Dortmund)

  • Dimitri Scheftelowitsch

    (Informatik IV, TU Dortmund)

Abstract

We consider sets of Markov decision processes (MDPs) with shared state and action spaces and assume that the individual MDPs in such a set represent different scenarios for a system’s operation. In this setting, we solve the problem of finding a single policy that performs well under each of these scenarios by considering the weighted sum of value vectors for each of the scenarios. Several solution approaches as well as the general complexity of the problem are discussed and algorithms that are based on these solution approaches are presented. Finally, we compare the derived algorithms on a set of benchmark problems.

Suggested Citation

  • Peter Buchholz & Dimitri Scheftelowitsch, 2019. "Computation of weighted sums of rewards for concurrent MDPs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 89(1), pages 1-42, February.
    • Handle: RePEc:spr:mathme:v:89:y:2019:i:1:d:10.1007_s00186-018-0653-1
    DOI: 10.1007/s00186-018-0653-1
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    References listed on IDEAS

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    Cited by:

    1. Hossein Hashemi Doulabi & Shabbir Ahmed & George Nemhauser, 2022. "State-Variable Modeling for a Class of Two-Stage Stochastic Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 354-369, January.

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