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In this paper we study the infinite planning horizon, countable state, semi·Markov decision processes (SMDP's) with the incomplete state observation under the average cost criterion. We show that this model can be transformed to ordinary SMDP's, i.e., SMDP's with the complete state observation. Furthermore, when the action :;pace is assumed to be finite, we present some sufficient conditions under which there exists an optimal stationary I-policy, and the method of successive approximations is applicable for obtaining a solution of the optimality equation.

SEMI-MARKOV DECISION PROCESSES WITH INCOMPLETE STATE OBSERVATION : AVERAGE COST CRITERION