Discounted MDP’s: Distribution Functions and Exponential Utility Maximization

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 1987 English Publisher:Society for Industrial & Applied Mathematics (SIAM)Journal:SIAM Journal on Control and Optimization, volume 25, pages 49-62 (issn: 0363-0129, eissn: 1095-7138,

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Authors: Chung, Kun-Jen; Sobel, Matthew J.;

doi: 10.1137/0325004

Discounted MDP’s: Distribution Functions and Exponential Utility Maximization

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Abstract

The present value of the rewards associated with a discrete-time Markov process has a probability distribution which depends on the initial state. The first part of the paper applies fixed point theory to a system of equations for the distribution functions of the present value. The second part of the paper expands the model to a Markov decision process (MDP) and considers the maximization of the expected utility of the present value when the utility function is exponential.

Related Organizations

Georgia Institute of Technology
United States

Keywords

Markov and semi-Markov decision processes, fixed point, discrete-time Markov process

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