Geodesic
Methods of rules selection with backward chaining in static expert systems
Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 156 (2014) no. 3, pp. 142-151
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The article discusses the problem of optimizing the solution search process in a static expert system. The research on the stage of backward chaining for rule selection and execution is conducted. A method of statistics collection for analysis of this stage is given. The results are presented in the form of a comparative analysis of the four methods of selecting rules for knowledge bases in three categories of tasks. The most efficient methods are identified in each category. Based on these methods, a version of the mixed method and an algorithm of backward chaining minimizing the number of rules used in solving the tasks under study are proposed.
Keywords: expert system, knowledge base, inference engine, backward chaining, production knowledge representation. 
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A. M. Yurin; M. P. Denisov. Methods of rules selection with backward chaining in static expert systems. Učënye zapiski Kazanskogo universiteta. Seriâ Fiziko-matematičeskie nauki, Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, Tome 156 (2014) no. 3, pp. 142-151. http://geodesic.mathdoc.fr/item/UZKU_2014_156_3_a14/

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