Credibilistic Markov decision processes: The average case

Authors:
Masayuki Kageyama
Affiliations:
The Institute of Statistical Mathematics, Japan
Venue:
Journal of Computational and Applied Mathematics
Year:
2009

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Abstract

Using a concept of random fuzzy variables in credibility theory, we formulate a credibilistic model for unichain Markov decision processes under average criteria. And a credibilistically optimal policy is defined and obtained by solving the corresponding non-linear mathematical programming. Also we give a computational example to illustrate the effectiveness of our new model.