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Stochastic revision opportunities in Markov decision problems

Author

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  • Yevgeny Tsodikovich

    (Tel-Aviv University)

  • Ehud Lehrer

    (Tel-Aviv University)

Abstract

We extend Markov Decision Processes to situations where the actions are binding and cannot be changed in every period. Instead, the decision maker can revise her actions at random times. We consider two slightly different models. In the first, the revision opportunity appears at a specific stage at which the decision maker can change her action, but is lost if not used. The action taken then remains constant until the next revision opportunity comes up. In the second model, the revision opportunity remains open and can be used at any time after it appears. Only when the action is changed, it becomes binding again for another random period. We compare between different stochastic revision processes and characterize when one is always preferred to another.

Suggested Citation

  • Yevgeny Tsodikovich & Ehud Lehrer, 2019. "Stochastic revision opportunities in Markov decision problems," Annals of Operations Research, Springer, vol. 279(1), pages 251-270, August.
    • Handle: RePEc:spr:annopr:v:279:y:2019:i:1:d:10.1007_s10479-019-03252-9
    DOI: 10.1007/s10479-019-03252-9
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    Cited by:

    1. Yevgeny Tsodikovich, 2021. "The worst-case payoff in games with stochastic revision opportunities," Annals of Operations Research, Springer, vol. 300(1), pages 205-224, May.

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    More about this item

    Keywords

    Markov decision process; Stochastic dominance; Commitment; Exogenous timing;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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