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Markovian Decision Processes with Probabilistic Observation of States

Jay Satia, Roy E. Lave

Abstract

This is a study of finite state discrete time discounted Markovian decision process when the states are probabilistically observed. A model of this process is formulated, and an implicit enumeration algorithm is presented which optimizes the total expected discounted reward given the initial state. Several numerical examples are presented.

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Key concepts: Probabilistic logic, Markov process, Markov decision process, Enumeration, State (computer science), Mathematical optimization, Process (computing), Applied mathematics