A relaxed approach to simplification in genetic programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6021 LNCS, Issue , 2010, Pages 110-121

  Johnston, Mark ^a   Liddle, Thomas ^a   Zhang, Mengjie ^b  

^a School of Mathematics   (New Zealand)

^b VICTORIA UNIVERSITY OF WELLINGTON   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); GENETIC ALGORITHMS; STATISTICAL TESTS;

ACCEPTANCE CRITERIA; CLASSIFICATION ACCURACY; CLASSIFICATION DATASETS; CPU TIME; PROGRAM SIMPLIFICATION; SIMPLIFICATION METHOD; TRAINING EXAMPLE; TREE-BASED;

GENETIC PROGRAMMING;

EID: 77952316832     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12148-7_10     Document Type: Conference Paper

References (20)

1. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, Cambridge (1992)
2. Blickle, T., Thiele, L.: Genetic programming and redundancy. In: Hopf, J. (ed.) Genetic Algorithms within the Framework of Evolutionary Computation, Max- Planck-Institut für Informatik (MPI-I-94-241), pp. 33-38 (1994)
3. Dignum, S., Poli, R.: Operator equalisation and bloat free GP. In: O'Neill, M., Vanneschi, L., Gustafson, S., Esparcia Alćazar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol.4971, pp. 110-121. Springer, Heidelberg (2008)
4. Dignum, S., Poli, R.: Crossover, sampling, bloat and the harmful effects of size limits. In: O'Neill, M., Vanneschi, L., Gustafson, S., Esparcia Alćazar, A.I., De Falco, I., Della Cioppa, A., Tarantino, E. (eds.) EuroGP 2008. LNCS, vol.4971, pp. 158-169. Springer, Heidelberg (2008)
5. Poli, R.: A simple but theoretically-motivated method to control bloat in genetic programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol.2610, pp. 204-217. Springer, Heidelberg (2003)
6. Soule, T., Foster, J.A., Dickinson, J.: Code growth in genetic programming. In: Koza, J.R., et al. (eds.) Genetic Programming 1996: Proceedings of the First Annual Conference, Stanford University, CA, USA, pp. 215-223. MIT Press, Cambridge (1996)
7. Soule, T., Heckendorn, R.B.: An analysis of the causes of code growth in genetic programming. Genetic Programming and Evolvable Machines, 283-309 (2002)
8. Streeter, M.J.: The root causes of code growth in genetic programming. In: Ryan, C., Soule, T., Keijzer, M., Tsang, E.P.K., Poli, R., Costa, E. (eds.) EuroGP 2003. LNCS, vol.2610, pp. 443-454. Springer, Heidelberg (2003)
9. Crane, E.F., McPhee, N.F.: The effects of size and depth limits on tree based genetic programming. In: Yu, T., et al. (eds.) Genetic Programming Theory and Practice III. Genetic Programming, vol.9, pp. 223-240. Springer, Heidelberg (2005)
10. Nordin, P., Banzhaf, W.: Complexity compression and evolution. In: Eshelman, L. (ed.) Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA 1995), Pittsburgh, PA, USA, pp. 310-317. Morgan Kaufmann, San Francisco (1995)
11. Zhang, B.T., Mühlenbein, H.: Balancing accuracy and parsimony in genetic programming. Evolutionary Computation 3(1), 17-38 (1995)
12. Luke, S., Panait, L.: Lexicographic parsimony pressure. In: Langdon, W.B., et al. (eds.) Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation (GECCO 2002), New York, pp. 829-836. Morgan Kaufmann, San Francisco (2002)
13. Hooper, D., Flann, N.S.: Improving the accuracy and robustness of genetic programming through expression simplification. In: Koza, J.R., et al. (eds.) Genetic Programming 1996: Proceedings of the First Annual Conference, p. 428 (1996)
14. Wong, P., Zhang, M.: Algebraic simplification of GP programs during evolution. In: Keijzer, M., et al. (eds.) Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (GECCO 2006), Seattle, Washington, USA, July 8-12, vol.1, pp. 927-934. ACM Press, New York (2006)
15. Zhang, M., Wong, P., Qian, D.: Online program simplification in genetic programming. In: Wang, T.-D., Li, X., Chen, S.-H., Wang, X., Abbass, H.A., Iba, H., Chen, G.-L., Yao, X. (eds.) SEAL 2006. LNCS, vol.4247, pp. 592-600. Springer, Heidelberg (2006)
16. Kinzett, D., Zhang,M., Johnston,M.: Using numerical simplification to control bloat in genetic programming. In: Li, X., Kirley, M., Zhang, M., Green, D., Ciesielski, V., Abbass, H.A.,Michalewicz, Z., Hendtlass, T., Deb,K., Tan, K.C., Branke, J., Shi, Y. (eds.) SEAL 2008. LNCS, vol.5361, pp. 493-502. Springer, Heidelberg (2008)
17. Song, A., Chen, D., Zhang, M.: Bloat control in genetic programming by evaluating contribution of nodes. In: Raidl, G., et al. (eds.) Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO 2009), Montreal, pp. 1893-1894. ACM, New York (2009)
18. Forina, M., Leardi, R., Armanino, C., Lanteri, S.: PARVUS: An Extendable Package of Programs for Data Exploration, Classification and Correlation. Elsevier, Amsterdam (1988)
19. Asuncion, A., Newman, D.J.: UCI Machine Learning Repository (2007), http://www.ics.uci.edu/~mlearn/MLRepository.html
20. Zhang, M., Ciesielski, V.: Genetic programming for multiple class object detection. In: Foo, N.Y. (ed.) AI 1999. LNCS (LNAI), vol.1747, pp. 180-192. Springer, Heidelberg (1999)