Verification of Command and Control Models

Command and control models, often represented as rules or fuzzy rules, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of command and control models. Based on an analysis of the characteristics of command and control models, this paper presents a fuzzy causality diagram-based verification method for command and control models. Firstly, a formal description method is developed to describe command and control models. Secondly, formally described command and control models are mapped to fuzzy causality diagram. Thirdly, formal verification criteria for command and control models are developed in order to validly and formally verify them, based on which verification is grouped into two classes: weak verification and strong verification. Finally, algorithms for weak and strong verification are developed, thus implementing formal verification of command and control models.

[1]  Brooke H. McNally An approach to human behavior modeling in an air force simulation , 2005, Proceedings of the Winter Simulation Conference, 2005..

[2]  Ming Yang,et al.  Verification and Validation of Artificial Neural Network Models , 2005, Australian Conference on Artificial Intelligence.

[3]  Pedro Meseguer,et al.  Incremental Verification of Rule-Based Expert Systems , 1992, ECAI.

[4]  Walton A. Perkins,et al.  Checking an Expert Systems Knowledge Base for Consistency and Completeness , 1985, IJCAI.

[5]  Qin Zhang Probabilistic reasoning based on dynamic causality trees/diagrams , 1994 .

[6]  Ming Yang,et al.  Verification and validation of AI simulation systems , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[7]  Edward H. Shortliffe,et al.  An Approach to Verifying Completeness and Consistency in a Rule-Based Expert System , 1982, AI Mag..

[8]  Jin-Fu Chang,et al.  Knowledge Representation Using Fuzzy Petri Nets , 1990, IEEE Trans. Knowl. Data Eng..

[9]  Marie-Christine Rousset,et al.  On the consistency of knowledge bases: the COVADIS system , 1988, Comput. Intell..