1. Holland, J.H.: Escaping brittleness: the possibilities of general purpose learning algorithms applied to parallel rule-based systems. Mach. Learn. Artif. Intell. Approach 2, 593–623 (1986)
2. Kovacs, T.: Evolving optimal populations with XCS classifier systems. Technical report CSR-96-17 and CSRP-96-17, School of Computer Science, University of Birmingham, Birmingham, U.K. (1996)
3. Butz, M.V., Goldberg, D.E., Tharakunnel, K.: Analysis and improvement of fitness exploitation in XCS: bounding models, tournament selection, and bilateral accuracy. Evol. Comput. 11(3), 239–277 (2003)
4. Borna, K., Hoseini, S., Aghaei, M.A.M.: Customer satisfaction prediction with Michigan-style learning classifier system. SN Appl. Sci. 1(11), 1450 (2019)
5. Proceedings in Adaptation, Learning and Optimization;M Nakata,2017