Comparing learning classifier systems and Genetic Programming: a case study

Abstract 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.