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The Relations Among Potentials, Perturbation Analysis, and Markov Decision Processes
Authors:Xi-Ren Cao
Affiliation:(1) The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
Abstract:This paper provides an introductory discussion for an important concept, the performance potentials of Markov processes, and its relations with perturbation analysis (PA), average-cost Markov decision processes (MDP), Poisson equations, agr-potentials, the fundamental matrix, and the group inverse of the transition matrix (or the infinitesimal generators). Applications to single sample path-based performance sensitivity estimation and performance optimization are also discussed. On-line algorithms for performance sensitivity estimates and on-line schemes for policy iteration methods are presented. The approach is closely related to reinforcement learning algorithms.
Keywords:Policy iterations  Poisson equations  agr-potentials" target="_blank">gif" alt="agr" align="BASELINE" BORDER="0">-potentials  group inverse  fundamental matrices  on-line optimization  reinforcement learning
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