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Vector-valued Markov decision processes and the systems of linear inequalities

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  • Wakuta, Kazuyoshi

Abstract

For a vector-valued Markov decision process, we characterize optimal (deterministic) stationary policies by systems of linear inequalities and present an algorithm for finding all optimal stationary policies from among all randomized, history-remembering ones. The algorithm consists of improving the policies and of checking the optimality of a policy by solving the associated system of linear inequalities via Fourier elimination.

Suggested Citation

  • Wakuta, Kazuyoshi, 1995. "Vector-valued Markov decision processes and the systems of linear inequalities," Stochastic Processes and their Applications, Elsevier, vol. 56(1), pages 159-169, March.
    • Handle: RePEc:eee:spapps:v:56:y:1995:i:1:p:159-169
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    References listed on IDEAS

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    1. Wakuta, Kazuyoshi, 1992. "Optimal stationary policies in the vector-valued Markov decision process," Stochastic Processes and their Applications, Elsevier, vol. 42(1), pages 149-156, August.
    2. Nagata Furukawa, 1980. "Characterization of Optimal Policies in Vector-Valued Markovian Decision Processes," Mathematics of Operations Research, INFORMS, vol. 5(2), pages 271-279, May.
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    Cited by:

    1. Hernández-Lerma, Onésimo & Romera, Rosario, 2000. "Pareto optimality in multiobjective Markov control processes," DES - Working Papers. Statistics and Econometrics. WS 9865, Universidad Carlos III de Madrid. Departamento de Estadística.

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    2. Hernández-Lerma, Onésimo & Romera, Rosario, 2000. "Pareto optimality in multiobjective Markov control processes," DES - Working Papers. Statistics and Econometrics. WS 9865, Universidad Carlos III de Madrid. Departamento de Estadística.

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