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As rule-based systems RBS technologygains wider acceptance, the need to create and maintain large knowledge baseswill assume greater importance. Demonstrating a rule base to be free from errorremains one of the obstacles to the adoption of this technology. In the pastseveral years, a vast body of research has been carried out in developingvarious graphical techniques such as utilizing Petri Nets to analyzestructural errors in rule-based systems, which utilize propositional logic.Four typical errors in rule-based systems are redundancy, circularity,incompleteness, and inconsistency. Recently, a DNA-based computing approach todetect these errors has been proposed. That paper presents algorithms which areable to detect structural errors just for special cases. For a rule base, whichcontains multiple starting nodes and goal nodes, structural errors are notremoved correctly by utilizing the algorithms proposed in that paper andalgorithms lack generality. In this study algorithms mainly based on Adleman’soperations, which are able to detect structural errors, in any form that theymay arise in rule base, are presented. The potential of applying our algorithmis auspicious giving the operational time complexity of On*Max{q, K, z}, inwhich n is the number of fact clauses; q is the number of rules in the longestinference chain; K is the number of tubes containing antecedents which arecomprised of distinct number of starting nodes; and z denotes the maximumnumber of distinct antecedents comprised of the same number of starting nodes.


DNA Computing, Rule-Based Systems, Rule Verification, Structural Errors

Cite this paper

Madahian, B. , Salighehdar, A. and Amini, R. 2015 Applying DNA Computation to Error Detection Problem in Rule-Based Systems. Journal of Intelligent Learning Systems and Applications, 7, 21-36. doi: 10.4236-jilsa.2015.71003.

Autor: Behrouz Madahian1, Amin Salighehdar2, Reza Amini3



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