Discounted Approximations for Risk-Sensitive Average Criteria in Markov Decision Chains with Finite State Space

• 成果类型: Article
• 署名作者: Cavazos-Cadena, Rolando; Hernandez-Hernandez, Daniel
• 署名单位: CIMAT - Centro de Investigacion en Matematicas
• 刊物名称: MATHEMATICS OF OPERATIONS RESEARCH
• ISSN/ISSBN: 0364-765X
• DOI: 10.1287/moor.1100.0476
• 发表日期: 2011
• 页码: 133-146
• 关键词: optimal stationary policies; optimality; cost; EXISTENCE

摘要

This work concerns Markov decision processes with finite state space and compact action set. The performance of a control policy is measured by a risk-sensitive average cost criterion and, under standard continuity-compactness conditions, it is shown that the discounted approximations converge to the optimal value function, and that the superior and inferior limit average criteria have the same optimal value function. These conclusions are obtained for every nonnull risk-sensitivity coefficient, and regardless of the communication structure induced by the transition law.