Abstract
Learning classifier systems (LCSs) are rule-based, evolutionary learning systems. Recently, there is a growing interest among the researchers in exploring LCSs implemented in a real-valued environment, due to its practical applications. This paper describes the use of a real-valued Grammar-based Classifier System (rGCS) in a task of 2D function approximation. rGCS is based on Grammar-based Classifier System (GCS), which was originally used to process context free grammar sentences. In this paper, we propose an extension to rGCS, called Simple Accept Radius (SAR) mechanism, that filters invalid and unexpected input real values. Performance evaluations show that the additional Simple Accept Radius mechanism enables rGCS to accurately approximate 2D discontinuous function. Performance comparisons with another real-valued LCS show that rGCS yields competitive performance.
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References
Butz, M.: Kernel-based, Ellipsoidal Conditions in the Real-valued XCS Classifier System. In: Proceedings of the 2005 Conference on Genetic and Evolutionary Computation, pp. 1835–1842. ACM (2005)
Cielecki, L., Unold, O.: Real-valued GCS Classifier System. International Journal of Applied Mathematics and Computer Science 17(4), 539–547 (2007)
Cielecki, L., Unold, O.: Modified Himmelblau Function Classification with RGCS System. In: Proc. of 8th International Conference on Hybrid Intelligent Systems, HIS 2008, pp. 879–884. IEEE (2008)
Gold, E.: Language Identification in the Limit. Information and Control 10(5), 447–474 (1967)
Holland, J.: Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. U. Michigan Press (1975)
Holland, J.: Adaptation. In: Rosen, R., Snell, F. (eds.) Progress in Theoretical Biology. Academic Press (1976)
Unold, O.: Context-free Grammar Induction with Grammar-based Classifier System. Archives of Control Science 15(4), 681–690 (2005)
Unold, O., Cielecki, L.: Grammar-based Classifier System. In: Issues in Intelligent Systems: Paradigms, pp. 273–286 (2005)
Unold, O., Cielecki, L.: How to use Crowding Selection in Grammar-based Classifier System. In: Proceedings of 5th International Conference on Intelligent Systems Design and Applications, ISDA 2005, pp. 124–129. IEEE (2005)
Unold, O.: Playing a Toy-Grammar with GCS. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005, Part II. LNCS, vol. 3562, pp. 300–309. Springer, Heidelberg (2005)
Wilson, S.W.: Get Real! XCS with Continuous-Valued Inputs. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 1999. LNCS (LNAI), vol. 1813, pp. 209–219. Springer, Heidelberg (2000)
Younger, D.: Recognition and Parsing of Context-free Languages in Time n3. Information and Control 10(2), 189–208 (1967)
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Cielecki, L., Unold, O. (2012). 2D Discontinuous Function Approximation with Real-Valued Grammar-Based Classifier System. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_2
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DOI: https://doi.org/10.1007/978-3-642-31588-6_2
Publisher Name: Springer, Berlin, Heidelberg
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