Abstract
This paper demonstrates that, with minimal modifications, a classifier system can be made to operate just as an ant colony optimizer does for solving the TSP. The paper contains a formal proof of this result, and suggests that the modifications made could be useful in other ways. In effect, the paper suggests that there may be a new role for classifier systems in optimization, inspired by the way that ant colony optimizers have achieved their successes. The paper also suggests that there may be ways suggested by classifier systems to modify ant colony optimization practice.
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References
Ant Colony Optimizers: A web site maintained by Marco Dorigo that provides information about the field of ant colony optimizers can be found at http://www.aco-metaheuristic.org
Classifier Systems: A web site maintained by Alwyn Barry that provides access to the field of learning classifier systems can be found at http://lcsweb.cs.bath.ac.uk
Davis, L., Wilson, S., Orvosh, D.: Temporary Memory for Examples Can Speed Learning in a Simple Adaptive System. In: Wilson, S. (ed.) Proceedings of the Second International Conference on the Simulation of Adaptive Behavior, MIT Press, Cambridge (1993)
Dorigo, M., Gambardella, L.M.: Ant Colonies for the Traveling Salesman Problem. BioSystems 43, 73–81 (1997)
Dorigo, M., Maniezzo, V., Colorni, A.: The Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B 26(1), 29–41 (1996)
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© 2007 Springer Berlin Heidelberg
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Davis, L. (2007). A Formal Relationship Between Ant Colony Optimizers and Classifier Systems. In: Kovacs, T., Llorà, X., Takadama, K., Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS IWLCS IWLCS 2003 2004 2005. Lecture Notes in Computer Science(), vol 4399. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71231-2_17
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DOI: https://doi.org/10.1007/978-3-540-71231-2_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71230-5
Online ISBN: 978-3-540-71231-2
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