Abstract
In recent years a new evolutionary algorithm for optimization in continuos spaces called Differential Evolution (DE) has developed. DE turns out to need only few evaluation steps to minimize a function. This makes it an interesting candidate for problem domains with high computational costs as for instance in the automatic generation of programs. In this paper a DE-based tree discovering algorithm called Tree based Differential Evolution (TreeDE) is presented. TreeDE maps full trees to vectors and represents discrete symbols by points in a real-valued vector space providing this way all arithmetical operations needed for the different DE schemes. Because TreeDE inherits the ’speed property’ of DE, it needs only few evaluations to find suitable trees which produce comparable and better results as other methods.
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References
Abbass, H.A., Hoai, N.X., McKay, R.I.: AntTAG: A new method to compose computer programs using colonies of ants. In: IEEE Congress on Evolutionary Computation (2002)
Koza, J.R.: Genetic Programming: On the Programming of Computers by Natural Selection. MIT Press, Cambridge (1992)
O’Neill, M., Brabazon, A.: Grammatical Differential Evolution. In: Proc. International Conference on Artificial Intelligence. CSEA Press, Las Vegas (2006)
Page, J., Poli, R., Langdon, W.B.: Smooth Uniform Crossover with Smooth Point Mutation in Genetic Programming: A Preliminary Study. In: Langdon, W.B., Fogarty, T.C., Nordin, P., Poli, R. (eds.) EuroGP 1999. LNCS, vol. 1598, pp. 39–48. Springer, Heidelberg (1999)
Poli, R., McPhee, N.F.: General Schema theory for genetic programming with subtree-swapping crossover: Part I. Evolutionary Computation 11(1), 53–66 (2003)
Shan, Y., Abbass, H., McKay, R.I., Essam, D.: AntTAG: a further study. In: Proc. 6th Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems, Canberra, Australia (2002)
Storn, R., Price, K.: Differential Evolution - A Simple and Efficient Adaptive Scheme for Global Optimization Over Continuous Spaces, Univ. California, Berkeley, ICSI, Technical Report TR-95-012 (March 1995), ftp://ftp.icsi.berkeley.edu/pub/techreports/1995/tr-95-012.pdf
Storn, R.: On the Usage of Differential Evolution for Function Optimization. In: 1996 Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS 1996), Berkeley, pp. 519–523. IEEE, USA (1996)
Storn, R., Price, K.: Differential Evolution - A Simple and Efficient Heuristic for global Optimization over Continuous Spaces. Journal of Global Optimization 11(4), 341–359 (1997)
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Veenhuis, C.B. (2009). Tree Based Differential Evolution. In: Vanneschi, L., Gustafson, S., Moraglio, A., De Falco, I., Ebner, M. (eds) Genetic Programming. EuroGP 2009. Lecture Notes in Computer Science, vol 5481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01181-8_18
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DOI: https://doi.org/10.1007/978-3-642-01181-8_18
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