We study a robust optimal control of discrete time Markov chains with finite terminal T and bounded costs using probability distortion. The time inconsistency of these operators and hence its lack of dynamic programming are discussed. Due to that, dynamic versions of these operators are introduced and its availability for dynamic programming are demonstrated. Based on dynamic programming algorithm, existence of the optimal policy is justified and an application of the theory to portfolio optimization is also presented.
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