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Full reinforcement operators in aggregation techniques

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2 Author(s)
R. R. Yager ; Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA ; A. Rybalov

We introduce the concept of upward reinforcement in aggregation as one in which a collection of high scores can reinforce or corroborate each other to give an even higher score than any of the individual arguments. The concept of downward reinforcement is also introduced as one in which low scores reinforce each other. Our concern is with full reinforcement aggregation operators, those exhibiting both upward and downward reinforcement. It is shown that the t-norm and t-conorm operators are not full reinforcement operators. A class of operators called fixed identity MICA operators are shown to exhibit the property of full reinforcement. We present some families of these operators. We use the fuzzy system modeling technique to provide further examples of these operators

Published in:

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)  (Volume:28 ,  Issue: 6 )