Albert Orriols-Puig
ABSTRACT
In this paper, we derive models of the selection pressure in XCS for proportionate (roulette wheel) selection and tournament selection. We show that these models can explain the empirical results that have been previously presented in the literature. We validate the models on simple problems showing that, (i) when the model assumptions hold, the theory perfectly matches the empirical evidence; (ii) when the model assumptions do not hold, the theory can still provide qualitative explanations of the experimental results.
- L. Bull. Simple markov models of the geneticalgorithm in classifier systems: Accuracy-based fitness. In Proceedings of the International Workshop on Learning Classifier Systems (IWLCS-2000), in the Joint Workshops of SAB 2000 and PPSN 2000, 2000. Extended abstract. Google Scholar
Digital Library
- M. Butz, D. E. Goldberg, and P. L. Lanzi. Bounding Learning Time in XCS. In Genetic and Evolutionary Computation - GECCO-2004, LNCS, Seattle, WA, USA, 26--30 June 2004. Springer-Verlag.Google Scholar
- M. Butz, D. E. Goldberg, and K. K. Tharakunnel. Analysis and Improvement of Fitness Exploitation in XCS: Bounding Models, Tournament Selection, and Bilateral Accuracy. Evolutionary Computation, 11(3):239--277, 2003. Google ScholarDigital Library
- M. Butz, D. G. Goldberg, P. L. Lanzi, and K. Sastry. Bounding the Population Size to Ensure Niche Support in XCS. Technical Report 2004033, Illinois Genetic Algorithms Laboratory - University of Illinois at Urbana-Champaign, Nov. 2004.Google Scholar
- M. V. Butz. Documentation of XCS+TS C-Code 1.2. Technical Report 2003023, Illinois Genetic Algorithm Laboratory (IlliGAL), University of Illinois at Urbana-Champaign, 2003.Google Scholar
- M. V. Butz, T. Kovacs, P. L. Lanzi, and S.W. Wilson. Toward a Theory of Generalization and Learning in XCS. IEEE Transaction on Evolutionary Computation, 8(1):28--46, Feb. 2004.Google ScholarDigital Library
- M. V. Butz, K. Sastry, and D. E. Goldberg. Strong, Stable, and Reliable Fitness Pressure in XCS due to Tournament Selection. Genetic Programming and Evolvable Machines, 6:53--77, 2005. Google ScholarDigital Library
- M. V. Butz and S. W. Wilson. An Algorithmic Description of XCS. Journal of Soft Computing, 6(3-4):144--153, 2002.Google ScholarCross Ref
- D. E. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, Mass., 1989. Google ScholarDigital Library
- D. E. Goldberg. The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, 2002. Google ScholarDigital Library
- D. E. Goldberg and K. Deb. A Comparative Analysis of Selection Schemes Used in Genetic Algorithms. In G. J. E. Rawlins, editor, FOGA, pages 69--93. Morgan Kaufmann, 1990.Google Scholar
- J. H. Holland. Adaptation in Natural and Artificial Systems. The University of Michigan Press, 1975. Google ScholarDigital Library
- J. Horn, D. E. Goldberg, and K. Deb. Implicit Niching in a Learning Classifier System: Nature's Way. Evolutionary Computation, 2(1):37--66, 1994.Google ScholarDigital Library
- F. Kharbat, L. Bull, and M. Odeh. Revisiting Genetic Selection in the XCS Learning Classifier System. In Congress on Evolutionary Computation, volume 3, pages 2061--2068, Edinburgh, UK, 2-5 September 2005. IEEE.Google Scholar
- A. Orriols-Puig, K. Sastry, P. L. Lanzi, D. E. Goldberg, and E. Bernadó-Mansilla. Modeling Selection Pressure in XCS for Proportionate and Tournament Selection. Technical report, IlliGAL Report No. 2007004, Urbana-Champaign IL 61801, USA, 2007.Google Scholar
- S. W. Wilson. Classifier Fitness Based on Accuracy. Evolutionary Computation, 3(2):149--175, 1995. http://prediction-dynamics.com/.Google ScholarDigital Library
- S. W. Wilson. Generalization in the XCS classifier system. In Genetic Programming 1998: Proceedings of the Third Annual Conference, pages 665--674. Morgan Kaufmann, 1998.Google Scholar
Index Terms
- Modeling selection pressure in XCS for proportionate and tournament selection
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