An Inheritance Procedure for a Knowledge Representation Scheme Based on Fuzzy Petri Nets

Knowledge about facts from the real world is very often uncertain, ambiguous and vague. As a result, the inference mechanism based on such facts generates uncertain and vague conclusions, hi this paper we describe a formal model of knowledge representation for uncertain and vague domains. The model is based on the theory of high-level fuzzy Petri nets (FPNs), and a fuzzy inheritance procedure that uses the dynamical properties of a FPN is proposed. The upper-time complexity of the proposed inheritance algorithm is O(nm), where n is the number of places (concepts) and m is the number of transitions (relations) in the scheme. An illustrative example of the inheritance procedure is presented.