Competitive and cooperative adaptive reasoning with fuzzy causal knowledge

In the current literature on knowledge-based diagnostic reasoning, two kind s of knowledge, experiential knowledge and causal knowledge, are generally acquired and widely used. In 1995, Ding and Gupta [8] proposed a new approa ch to fuzzy neural network-based adaptive reasoning with experiential knowl edge. In that paper a fuzzy neuronal model with composite fuzzy MAX-MIN neu rons was presented for the acquisition of experiential knowledge and fuzzy reasoning. In this paper, we present an architecture for a dynamic fuzzy ca usal neural network for dealing with fuzzy causal knowledge for diagnostic problems. The inhibitory and excitatory mechanism of computational neurons are employed to model the complex competitive and cooperative behaviors bet ween disorders in the process of causal fuzzy reasoning.