An Approach to Object Identification Using Fuzzy Expected Payoffs

Article type: Research Article

Authors: Kleyle, R. | de Korvin, A.

Affiliations: Department of Mathematical Sciences, Indiana University-Purdue University at Indianapolis, Indianapolis, IN 46202, e-mail: [email protected] | Department of Computer and Mathematical Sciences, University of Houston-Downtown, Houston, TX 77002

Abstract: Imprecise information regarding feature values of an unidentified object is obtained from information sources of varying reliability. This imprecise information is used to construct a fuzzy probability distribution over the set of environments, which consist of all possible combinations of feature values. A fuzzy payoff matrix is constructed in which the rows represent all possible objects and the columns represent all possible environments. A fuzzy expected payoff is computed for each object (i.e., row) in this matrix. Each fuzzy expected payoff is then intersected with a maximizing set, and the object is identified as the one for which this intersection has the highest percentage of optimal values according to a specific criterion.

DOI: 10.3233/IFS-1995-3406

Journal: Journal of Intelligent and Fuzzy Systems, vol. 3, no. 4, pp. 305-316, 1995