Abstract
Nowadays, Linguistic Modeling is considered to be one of the most important areas of application for Fuzzy Logic. It is accomplished by linguistic Fuzzy Rule-Based Systems, whose most interesting feature is the interpolative reasoning developed. This characteristic plays a key role in their high performance and is a consequence of the cooperation among the involved fuzzy rules.
A new approach that makes good use of this aspect inducing cooperation among rules is introduced in this chapter: the Cooperative Rules methodology. One of its interesting advantages is its flexibility allowing it to be used with different combinatorial search techniques. Thus, four specific metaheuristics are considered: simulated annealing, tabu search, genetic algorithms and ant colony optimization. Their good performance is shown when solving a real-world problem.
This research is supported by CICYT, project PB98-1319
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Casillas, J., Cordón, O., Herrera, F. (2002). Different Approaches to Induce Cooperation in Fuzzy Linguistic Models Under the COR Methodology. In: Bouchon-Meunier, B., Gutiérrez-RÃos, J., Magdalena, L., Yager, R.R. (eds) Technologies for Constructing Intelligent Systems 1. Studies in Fuzziness and Soft Computing, vol 89. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1797-3_25
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DOI: https://doi.org/10.1007/978-3-7908-1797-3_25
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