Revisiting Genetic Selection in the XCS Learning Classifier System
Faten F. Kharbat, Larry Bull, Mohammed Odeh · 2005
The XCS learning classifier system has traditionally used roulette wheel selection within its genetic algorithm component. Recently, tournament selection has been suggested as providing a number of benefits over the original scheme, particularly a robustness to parameter settings and problem noise. This paper revisits the comparisons made between the behavior of tournament and roulette wheel selection within XCS in a number of different situations. Results indicate that roulette wheel selection is competitive in terms of performance, stability and generated solution size if the appropriate parameters are used.