2007
DOI: 10.1016/j.fss.2007.04.006
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Fuzzy optimality relation for perceptive MDPs—the average case

Abstract: 7In this paper, the fuzzy perceptive model for average reward Markov decision processes is defined and a method of computing the corresponding fuzzy perceptive values is proposed. Under the minorization condition for fuzzy perceptive transition matrices, 9 it is characterized by the optimal average expected reward, called the average perceptive value, using a fuzzy optimality relation. Also, we give a simple numerical example. 11

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Cited by 2 publications
(2 citation statements)
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“…The perceptive analysis developed in this paper is related to our previous works. A model of stopping problems is formulated in Kurano et al (2004) and that of Markov decision processes is in Kurano et al (2005a) and Kurano et al (2005b). However the basic assumption implemented in the previous stopping problem is different from this paper.…”
Section: Introductionmentioning
confidence: 94%
“…The perceptive analysis developed in this paper is related to our previous works. A model of stopping problems is formulated in Kurano et al (2004) and that of Markov decision processes is in Kurano et al (2005a) and Kurano et al (2005b). However the basic assumption implemented in the previous stopping problem is different from this paper.…”
Section: Introductionmentioning
confidence: 94%
“…Kurano et al [8,9] have described the ambiguous information for the unknown transition probability matrices by fuzzy sets and developed the theory of Pareto-optimization based on Zadeh's extension principle [2,19]. Also, by the same idea as above Kageyama [7] has treated the fuzzy information by a fuzzification operator with a deviation parameter and considered the model-identification problem for various values of the deviation parameter.…”
Section: Introductionmentioning
confidence: 99%