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Adaptive fuzzy Petri nets for dynamic knowledge representation and inference.

Li, X.; Lara-Rosano, F.

In: Expert System Applications, Vol. 19, No. 3, pages 235-241. 2000.

Abstract: Knowledgs in some fields like medicine, science and engineering is very dynamic because of the continuous contributions of research and development. Therefore, it would be very useful to design knowledge-based systems capable to be adjusted like human cognition and thinking, according to knowledge dynamics. Aiming at this objective, a mode generalized fuzzy Petri net model for expert systems is proposed, which is called AFPN (Adaptive Fuzzy Petri Net). This model has both the features of fuzzy net and the learning ability of a neural network. Being trained, an AFPN model can be used for dynamic knowledge representation and inference. After the introduction of the AFPN model, the reasoning algorithm and the weight learning algorithm are developed. An example is included as an illustration.

Keywords: dynamic knowledge representation, fuzzy Petri nets, neural nets.

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