By Dilip P. Ahalpara, Abhijit Sen (auth.), Sara Silva, James A. Foster, Miguel Nicolau, Penousal Machado, Mario Giacobini (eds.)
This e-book constitutes the refereed court cases of the 14th ecu convention on Genetic Programming, EuroGP 2011, held in Torino, Italy, in April 2011 co-located with the Evo* 2011 occasions.
This 20 revised complete papers awarded including nine poster papers have been conscientiously reviewed and chosen from fifty nine submissions. the big variety of themes during this quantity mirror the present nation of study within the box, together with representations, thought, novel operators and strategies, self association, and applications.
Read Online or Download Genetic Programming: 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011. Proceedings PDF
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Extra resources for Genetic Programming: 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011. Proceedings
As only ﬁve distinct ﬁtness values exist in our LGP system, this form of ﬁtness assignment would add a new layer of robustness and evolvability to the analysis. Specifically, this layer would consist of a set of vertices that each comprise multiple phenotypes, and links between these vertices would capture all mutational events that lead from one ﬁtness value to another. While ﬁtnesss would therefore modify the transition probabilities between phenotypes, selection would modify the transition probabilities between ﬁtness values.
For %PPB the RMSE on the training set steadily decreases during the whole evolution, while the RMSE on the test set is decreasing until generation 50, and then increasing until generation 500, also showing some oscillations. We conclude that GP has a worse generalization ability for LD50 and %PPB than for %F. Let us now focus on the curves representing GBC and 1-GBLA. Both GBC and 1-GBLA are increasing after generation 30 for LD50, steadily decreasing (except for the initial part of the run) for %F and increasing (except for the first 50 generations) for %PPB.
1 Results Statistical Characteristics of Genotype and Phenotype Space To characterize the genotype and phenotype spaces of the two-input, one-output LGP system of L = 4 instructions, we exhaustively enumerated the size and structure of the genotype networks corresponding to each of the 228 individual genotypes. In Fig. 2, we depict the corresponding phenotype network. The network is fully connected, such that any phenotype can be reached directly from any other. However, the number of non-neutral point mutations between phenotypes, depicted by edge width, is heterogeneous.