Modelling Evolvability in Genetic Programming

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9594)

Abstract

We develop a tree-based genetic programming system capable of modelling evolvability during evolution through machine learning algorithms, and exploiting those models to increase the efficiency and final fitness. Existing methods of determining evolvability require too much computational time to be effective in any practical sense. By being able to model evolvability instead, computational time may be reduced. This will be done first by demonstrating the effectiveness of modelling these properties a priori, before expanding the system to show its effectiveness as evolution occurs.

Keywords

Genetic programming Evolvability Meta-learning Artificial neural networks 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Memorial University of NewfoundlandSt. John’sCanada

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