publication . Other literature type . Article . 1987

Discounted MDP's: distribution functions and exponential utility maximization

Kun-Jen Chung; Matthew J. Sobel;
  • Published: 01 Jan 1987
  • Publisher: Society for Industrial & Applied Mathematics (SIAM)
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.
Subjects
free text keywords: Control and Optimization, Applied Mathematics, Decision theory, Exponential utility, Mathematics, Phase-type distribution, Partially observable Markov decision process, Markov process, symbols.namesake, symbols, Continuous-time Markov chain, Mathematical optimization, Markov decision process, Expected utility hypothesis
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