Risk-Sensitive Markov Decision Processes

Ronald A. Howard and James E. Matheson
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Ronald A. Howard: Stanford University
James E. Matheson: Stanford Research Institute

Management Science, 1972, vol. 18, issue 7, 356-369

Abstract: This paper considers the maximization of certain equivalent reward generated by a Markov decision process with constant risk sensitivity. First, value iteration is used to optimize possibly time-varying processes of finite duration. Then a policy iteration procedure is developed to find the stationary policy with highest certain equivalent gain for the infinite duration case. A simple example demonstrates both procedures.

Date: 1972
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