Abstract Fuzzy Petri nets (FPNs) are a potential modeling technique for knowledge
representation and reasoning of rule-based expert systems. To date, many studies have …

Fuzzy Petri net (FPN) provides an extremely competent basis for the implementation of
computing reasoning processes and the modeling of systems with uncertainty. This paper …

With all the material available in the field of artificial intelligence (AI) and soft computing-
texts, monographs, and journal articles-there remains a serious gap in the literature. Until …

There has been a long-lasting misunderstanding in the literature of artificial intelligence and
uncertainty modeling, regarding the role of fuzzy set theory and many-valued logics. The …

This paper presents a fuzzy reasoning Petri net (FRPN) model to represent a fuzzy
production rule-based system. The issues of how to represent and reason about rules …

This paper presents a Weighted Fuzzy Petri Net model (WFPN) and proposes a weighted
fuzzy reasoning algorithm for rule-based systems based on Weighted Fuzzy Petri Nets. The …

Since knowledge in an expert system is vague and modified frequently, expert systems are
fuzzy and dynamic. It is very important to design a dynamic knowledge inference framework …

This handbook provides information about fundamental aspects of the field and explores the
myriad applications of fuzzy logic techniques and methods. It presents basic conceptual …

Knowledge 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 …

This paper presents a new model for unsupervised learning and reasoning on a special type
of cognitive maps realized with Petri nets. The unsupervised learning process in the present …