Complex Knowledge System Modeling Based on Hierarchical Fuzzy Petri Net
WI-IATW '07 Proceedings of the 2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops
INFERENCE PROCEDURES FOR FUZZY KNOWLEDGE REPRESENTATION SCHEME
Applied Artificial Intelligence
Intersection Search for a Fuzzy Petri Net-Based Knowledge Representation Scheme
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Agent-based resource discovery architecture for environmental emergency management
Expert Systems with Applications: An International Journal
A fuzzy Petri-nets model for computing with words
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Reversed fuzzy Petri nets and their application for fault diagnosis
Computers and Industrial Engineering
A recognition-inference procedure for a knowledge representation scheme based on fuzzy petri nets
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Composing web services enacted by autonomous agents through agent-centric contract net protocol
Information and Software Technology
| Hi-index | 0.00 |
Manipulation of perceptions is a remarkable human capability in a wide variety of physical and mental tasks under fuzzy or uncertain surroundings. Possibilistic reasoning can be treated as a mechanism that mimics human inference mechanisms with uncertain information. Petri nets are a graphical and mathematical modeling tool with powerful modeling and analytical ability. The focus of this paper is on the integration of Petri nets with possibilistic reasoning to reap the benefits of both formalisms. This integration leads to a possibilistic Petri nets model (PPN) with the following features. A possibilistic token carries information to describe an object and its corresponding possibility and necessity measures. Possibilistic transitions are classified into four types: inference transitions, duplication transitions, aggregation transitions, and aggregation-duplication transitions. A reasoning algorithm, based on possibilistic Petri nets, is also presented to improve the efficiency of possibilistic reasoning and an example related to diagnosis of cracks in reinforced concrete structures is used to illustrate the proposed approach.