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Constraint satisfaction using soft quantifiers

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  • Ronald R. Yager

Abstract

Fuzzy sets and other methods have been used to model a softening of constraints in constraint propagation (CP) problems. Here, we suggest an approach to the softening of the CP problem at the meta level, in the process used to aggregate the satisfactions to the individual constraints. We discuss the possibility of using soft quantifiers such as ‘most’ to guide the process of aggregating the satisfactions to the individual constraints. Use is made of the ability to represent these soft quantifiers by fuzzy sets and the ability to implement their authorized aggregation by the ordered weighted averaging operator. Copyright © 2004 John Wiley & Sons, Ltd.

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  • Ronald R. Yager, 2004. "Constraint satisfaction using soft quantifiers," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(3), pages 177-186, July.
    • Handle: RePEc:wly:isacfm:v:12:y:2004:i:3:p:177-186
    DOI: 10.1002/isaf.250
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    References listed on IDEAS

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    1. R. E. Bellman & L. A. Zadeh, 1970. "Decision-Making in a Fuzzy Environment," Management Science, INFORMS, vol. 17(4), pages 141-164, December.
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