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Comparing learning classifier systems and Genetic Programming: a case study

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Engineering Applications of Artificial Intelligence, 17 (2): 199--204 (2004)
DOI: doi:10.1016/j.engappai.2004.02.006

Аннотация

Genetic Algorithms has given rise to two new fields of research where (global) optimisation is of crucial importance: 'genetic based machine learning' (GBML) and 'genetic programming' (GP). An advanced implementation of GBML (Fuzzy Efficiency based Classifier System, FECS, developed by the authors) and GP (as defined by Koza) are both applied to the case study 'fibre-to-yarn production process'. Results for both systems are presented and compared. Finally, the GP generated equations are transformed into rule-sets similar to those obtained from FECS.

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