In this paper the execution of Fuzzy Knowledge Bases in the truth space is briefly analyzed. The computational efficiency of the process is significantly increased by means of a parameterized description based on the linguistic truth values described by Baldwin. This permits executing the Fuzzy Knowledge Base through operations involving only simple numerical values, thus avoiding the direct analytic manipulation of possibility distributions. A Petri Net-based formalism that permits representing both the Fuzzy Knowledge Base and different dynamic processes performed onto it (execution following different strategies, cycles and loops detection) is also presented. The paper focus on the algorithm for carrying out inferences in situations when information for all the input variables in the Fuzzy Knowledge Base is available.
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