rule-based programming

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Optimization of Production Systems using Genetic Algorithms

Journal Title, Volume, Page: 
International Journal of Computational Intelligence and Applications, Vol. 3, No. 3, pp. 233-248
Year of Publication: 
2003
Authors: 
Wael Mustafa
Department of Computer Science, Faculty of Engineering and Information Technology, An-Najah National University, Nablus, Palestine
Current Affiliation: 
Department of Computer Science, Faculty of Engineering and Information Technology, An-Najah National University, Nablus, Palestine
Preferred Abstract (Original): 
This paper presents a Genetic Algorithm for Production Systems Optimization (GAPSO). The GAPSO finds an ordering of Condition Elements (CEs) in the rules of a Production System (PS) that results in a (near) optimal PS with respect to execution time. Finding such an ordering can be difficult since there is often a large number of ways to order CEs in the rules of a PS. Additionally, existing heuristics to order CEs in many cases conflict with each other. The GAPSO is applicable to PSs in general and no assumptions are made about the matching algorithm or the interpreter that executes the PS. The results of applying the GAPSO to some example PSs are presented. In all examples, the GAPSO found an optimal ordering of CEs in a small number of iterations.
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