Tournament Selection: Stable Fitness Pressure in XCS

Although it is known from GA literature that proportionate selection is subject to many pitfalls, the LCS community somewhat adhered to proportionate selection. Also in the accuracy-based learning classifier system XCS, introduced by Wilson in 1995, proportionate selection is used. This paper identifies problem properties in which performance of proportionate selection is impaired. Consequently, tournament selection is introduced which makes XCS more parameter independent, noise independent, and more efficient in exploiting fitness guidance.

[1]  Stewart W. Wilson.  Get Real! XCS with Continuous-Valued Inputs , 1999, Learning Classifier Systems.

[2]  M. Pelikán,et al.  Analyzing the evolutionary pressures in XCS , 2001 .

[3]  Xavier Llorà,et al.  XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining , 2001, IWLCS.

[4]  Kenneth A. De Jong,et al.  Learning Concept Classification Rules Using Genetic Algorithms , 1991, IJCAI.

[5]  D. Goldberg,et al.  A practical schema theorem for genetic algorithm design and tuning , 2001 .

[6]  H. Crichton-Miller.  Adaptation , 1926 .

[7]  Martin V. Butz,et al.  An Algorithmic Description of XCS , 2000, IWLCS.

[8]  Hitoshi Iba,et al.  Genetic Programming 1998: Proceedings of the Third Annual Conference , 1999, IEEE Trans. Evol. Comput..

[9]  D. Cliff.  From animals to animats 3 : proceedings of the Third International Conference on Simulation of Adaptive Behavior , 1994 .

[10]  Stewart W. Wilson,et al.  Learning Classifier Systems, From Foundations to Applications , 2000 .

[11]  Pier Luca Lanzi,et al.  An Analysis of Generalization in the XCS Classifier System , 1999, Evolutionary Computation.

[12]  D.E. Goldberg,et al.  Classifier Systems and Genetic Algorithms , 1989, Artif. Intell..

[13]  David E. Goldberg,et al.  A Survey of Optimization by Building and Using Probabilistic Models , 2002, Comput. Optim. Appl..

[14]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[15]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[16]  Andrew W. Moore,et al.  Reinforcement Learning: A Survey , 1996, J. Artif. Intell. Res..

[17]  Stewart W. Wilson.  Generalization in the XCS Classifier System , 1998 .

[18]  Martin V. Butz,et al.  An algorithmic description of XCS , 2000, Soft Comput..

[19]  Alwyn Barry,et al.  A hierarchical XCS for long path environments , 2001 .

[20]  Martin J. Oates,et al.  A Preliminary Investigation of Modified XCS as a Generic Data Mining Tool , 2001, IWLCS.

[21]  M. Colombetti,et al.  An extension to the XCS classifier system for stochastic environments , 1999 .

[22]  Gilles Venturini,et al.  Adaptation in dynamic environments through a minimal probability of exploration , 1994 .

[23]  Martin V. Butz,et al.  How XCS evolves accurate classifiers , 2001 .

[24]  Stewart W. Wilson.  Classifier Fitness Based on Accuracy , 1995, Evolutionary Computation.