Symbolic Similarity Relations for Tuning Fully Integrated Fuzzy Logic Programs

Inspired by our previous experiences in the design of fuzzy logic languages not dealing yet with similarity relations, in this work we introduce a symbolic extension of FASILL (acronym of "Fuzzy Aggregators and Similarity Into a Logic Language"). Since one of the most difficult tasks when specifying a fuzzy logic program is determining the right weights/connectives used in the rules and the similarity relation of FASILL programs, our technique is able to symbolically execute them with unknown parameters, so that the user can guess the impact of their possible values in further developments. Then, it is possible to automatically tune such programs by appropriately substituting (with the concrete values that best satisfy the user's preferences) the symbolic constants appearing in their program rules and similarity relations.