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Conference Publication

Behavior-based Speciation in Classification with NeuroEvolution

Host Publication: 2020 IEEE World Congress on Computational Intelligence

Authors: E. Papavasileiou, J. Cornelis and B. Jansen

Publication Date: Sep. 2020

Number of Pages: 7


Abstract:

We propose a neuroevolutionary speciation mechanism that is applied on NeuroEvolution of Augmenting Topologies (NEAT) that solely evolves neural networks’ topology and weights and its extension HA-NEAT that also evolves activation functions. The new speciation mechanism is defined based on the behavior of the individuals rather than their topological similarity. Focusing on classification tasks we build artificial datasets of high complexity. Performance is described by (i) median classification accuracy, (ii) computational efficiency (number of generations) and (iii) network complexity (number of nodes and connections). The performance metrics are compared using Kruskal-Wallis hypothesis tests with Bonferroni correction. It is found that the proposed behavioral speciation mechanism outperforms the original speciation solving problems that were not solvable before or improving the accuracy and reducing the network complexity

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Dr. Ir. Evgenia Papavasileiou

+32 (0)02 629 168

epapavas@etrovub.be

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Prof. Dr. Ir. Jan Cornelis

+32 (0)02 629 293

jpcornel@etrovub.be

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Prof. Dr. Bart Jansen

+32 (0)02 629 103

bjansen@etrovub.be

more info

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