Abstract
In this paper we focus on machine-learning issues solved with Genetic Programming (GP). Excessive code growth or bloat often happens in GP, greatly slowing down the evolution process. In Pol03, Poli proposed the Tarpeian Control method to reduce bloat, but possible side-effects of this method on the generalization accuracy of GP hypotheses remained to be tested. In particular, since Tarpeian Control puts a brake on code growth, it could behave as a kind of Occam’s razor, promoting shorter hypotheses more able to extend their knowledge to cases apart from any learning steps.
To answer this question, we experiment Tarpeian Control with symbolic regression. The results are contrasted, showing that it can either increase or reduce the generalization power of GP hypotheses, depending on the problem at hand. Experiments also confirm the decrease in size of programs. We conclude that Tarpeian Control might be useful if carefully tuned to the problem at hand.
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References
Banzhaf, W., Langdon, W.B.: Some considerations on the reason for bloat. Genetic Programming and Evolvable Machines 3(1), 81–91 (2002)
Deb, K., Poli, R., Banzhaf, W., Beyer, H.-G., Burke, E., Darwen, P., Dasgupta, D., Floreano, D., Foster, J., Harman, M., Holland, O., Lanzi, P.L., Spector, L., Tettamanzi, A., Thierens, D., Tyrrell, A. (eds.): GECCO 2004. LNCS, vol. 3103. Springer, Heidelberg (2004)
Keijzer, M.: Improving symbolic regression with interval arithmetic and linear scaling. In: [RSK + 03] pp. 71–83, Essex (2003)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
Luke, S., Panait, L.: Lexicographic parsimony pressure. In: Langdon, W.B., Cantú-Paz, E., Mathias, K., Roy, R., Davis, D., Poli, R., Balakrishnan, K., Honavar, V., Rudolph, G., Wegener, J., Bull, L., Potter, M.A., Schultz, A.C., Miller, J.F., Burke, E., Jonoska, N. (eds.) GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, New York, July 9-13, 2002, pp. 829–836. Morgan Kaufmann Publishers, San Francisco (2002)
Luke, S.: Issues in Scaling Genetic Programming: Breeding Strategies, Tree Generation, and Code Bloat. PhD thesis, Department of Computer Science, University of Maryland, A. V. Williams Building, University of Maryland, College Park, MD 20742 USA (2000)
Luke, S.: Ecj 10: An evolutionnary computation research system in java (2003)
Mitchell, T.M.: Machine Learning. McGraw-Hill, New York (1997)
Panait, L., Luke, S.: Alternative bloat control methods. In : [DPB + 04] pp. 630–641 (2004)
Poli, R.: General schema theory for genetic programming with subtree-swapping crossover. In: Miller, J., Tomassini, M., Lanzi, P.L., Ryan, C., Tetamanzi, A.G.B., Langdon, W.B. (eds.) EuroGP 2001. LNCS, vol. 2038, pp. 143–159. Springer, Heidelberg (2001), http://link.springer-ny.com/link/service/series/0558/papers/2038/20380143.pdf
Poli, R.: A simple but theoretically-motivated method to control bloat in genetic programming. In: [RSK + 03] pp. 200–210 (2003)
Ryan, C., Soule, T., Keikzer, M., Tsang, E., Poli, R., Costa, E.: 6th European Conference, EuroGP. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol. 2610. Springer, Heidelberg (2003)
Streeter, M., Becker, L.A.: Automated discovery of numerical approximation formulae via genetic programming. In: [SGW + 01], pp. 147–154 (2001)
Spector, L., Goodman, E.D., Wu, A., Langdon, W.B., Voigt, H.-M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M.H., Burke, E. (eds.): Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), San Francisco, California, USA, Jul 7-11, 2001. Morgan Kaufmann, San Francisco (2001)
Topchy, A., Punch, W.F.: Faster genetic programming based on local gradient search of numeric leaf values. In: [SGW + 01] pp. 155–162 (2001)
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Mahler, S., Robilliard, D., Fonlupt, C. (2005). Tarpeian Bloat Control and Generalization Accuracy. In: Keijzer, M., Tettamanzi, A., Collet, P., van Hemert, J., Tomassini, M. (eds) Genetic Programming. EuroGP 2005. Lecture Notes in Computer Science, vol 3447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31989-4_18
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DOI: https://doi.org/10.1007/978-3-540-31989-4_18
Publisher Name: Springer, Berlin, Heidelberg
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