Abstract
This paper presents a formal model of the knowledge representation scheme KRFP based on the Fuzzy Petri Net (FPN) theory. The model is represented as an 11-tuple consisting of the components of the FPN and two functions that give semantic interpretations to the scheme. For the scheme a fuzzy recognition-inference procedure, based on the dynamical properties of the FPN and the inverse –KRFP scheme, is described in detail. An illustrative example of the fuzzy recognition algorithm for the knowledge base, designed by the KRFP, is given.
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Ribarić, S., Pavešić, N. (2006). A Recognition-Inference Procedure for a Knowledge Representation Scheme Based on Fuzzy Petri Nets. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_4
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DOI: https://doi.org/10.1007/11925231_4
Publisher Name: Springer, Berlin, Heidelberg
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