Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Barry, A.: A hierarchical XCS for long path environments. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001) (2001) 913–920
Bernadó, E., Llorà, X., Garrell, J.M.: XCS and GALE: A comparative study of two learning classifier systems and six other learning algorithms on classification tasks. In Lanzi, P.L., Stolzmann, W., Wilson, S.W., eds.: Advances in Learning Classifier Systems: 4th International Workshop, IWLCS 2001. Springer-Verlag, Berlin Heidelberg (2002) 115–132
Booker, L.B., Goldberg, D.E., Holland, J.H.: Classifier systems and genetic algorithms. Artificial Intelligence 40 (1989) 235–282
Butz, M.V., Kovacs, T., Lanzi, P.L., Wilson, S.W.: How XCS evolves accurate classifiers. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001) (2001) 927–934
Butz, M.V., Pelikan, M.: Analyzing the evolutionary pressures in XCS. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001) (2001) 935–942
Butz, M.V., Wilson, S.W.: An algorithmic description of XCS. In Lanzi, P.L., Stolzmann, W., Wilson, S.W., eds.: Advances in Learning Classifier Systems: Third International Workshop, IWLCS 2000. Springer-Verlag, Berlin Heidelberg (2001) 253–272
De Jong, K.A., Spears, W.M.: Learning concept classification rules using genetic algorithms. IJCAI-91 Proceedings of the Twelfth International Conference on Artificial Intelligence (1991) 651–656
Dixon, P.W., Corne, D.W., Oates, M.J.: A preliminary investigation of modified XCS as a generic data mining tool. In Lanzi, P.L., Stolzmann, W., Wilson, S.W., eds.: Advances in Learning Classifier Systems: 4th InternationalWorkshop, IWLCS 2001. Springer-Verlag, Berlin Heidelberg (2002) 133–150
Goldberg, D.E., Deb, K.: A comparative analysis of selection schemes used in genetic algorithms. Foundations of Genetic Algorithms (1991) 69–93
Goldberg, D.E., Sastry, K.: A practical schema theorem for genetic algorithm design and tuning. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001) (2001) 328–335
Holland, J.H.: Adaptation in natural and artificial systems. Universtiy of Michigan Press, Ann Arbor, MI (1975) second edition 1992.
Holland, J.H.: Adaptation. In Rosen, R., Snell, F., eds.: Progress in Theoretical Biology. Volume 4. Academic Press, New York (1976) 263–293
Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4 (1996) 237–258
Lanzi, P.L.: An analysis of generalization in the XCS classifier system. Evolutionary Computation 7 (1999) 125–149
Lanzi, P.L., Colombetti, M.: An extension to the XCS classifier system for stochastic environments. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99) (1999) 353–360
Pelikan, M., Goldberg, D.E., Lobo, F.: A survey of optimization by building and using probabilistic models. Computational Optimization and Applications 21 (2002) 5–20
Venturini, G.: Adaptation in dynamic environments through a minimal probability of exploration. From Animals to Animats 3: Proceedings of the Third International Conference on Simulation of Adaptive Behavior (1994) 371–381
Wilson, S.W.: Classifier fitness based on accuracy. Evolutionary Computation 3 (1995) 149–175
Wilson, S.W.: Generalization in the XCS classifier system. Genetic Programming 1998: Proceedings of the Third Annual Conference (1998) 665–674
Wilson, S.W.: Get real! XCS with continuous-valued inputs. In Lanzi, P.L., Stolzmann, W., Wilson, S.W., eds.: Learning Classifier Systems: From Foundations to Applications. Springer-Verlag, Berlin Heidelberg (2000) 209–219
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Butz, M.V., Sastry, K., Goldberg, D.E. (2003). Tournament Selection: Stable Fitness Pressure in XCS. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_83
Download citation
DOI: https://doi.org/10.1007/3-540-45110-2_83
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40603-7
Online ISBN: 978-3-540-45110-5
eBook Packages: Springer Book Archive