Abstract
In this study, two morphological representations in the genotype, a deterministic and a nondeterministic representation, are compared when evolving a neuronal morphology for a pattern recognition task. The deterministic approach represents the dendritic morphology explicitly as a set of partitions in the genotype which can give rise to a single phenotype. The nondeterministic method used in this study encodes only the branching probability in the genotype which can produce multiple phenotypes. The main result is that the nondeterministic method instigates the selection of more symmetric dendritic morphologies which was not observed in the deterministic method.
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Alva, P. et al. (2013). Evolution of Dendritic Morphologies Using Deterministic and Nondeterministic Genotype to Phenotype Mapping. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds) Artificial Neural Networks and Machine Learning – ICANN 2013. ICANN 2013. Lecture Notes in Computer Science, vol 8131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40728-4_40
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DOI: https://doi.org/10.1007/978-3-642-40728-4_40
Publisher Name: Springer, Berlin, Heidelberg
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