A peer-to-peer approach to genetic programming

Authors:
Juan Luis Jiménez Laredo;Daniel Lombraña González;Francisco Fernández De Vega;Maribel García Arenas;Juan Julián Merelo Guervós
Affiliations:
University of Granada, ATC-ETSIIT, Granada, Spain;University of Extremadura, Mérida, Spain;University of Extremadura, Mérida, Spain;University of Granada, ATC-ETSIIT, Granada, Spain;University of Granada, ATC-ETSIIT, Granada, Spain
Venue:
EuroGP'11 Proceedings of the 14th European conference on Genetic programming
Year:
2011

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Abstract

This paper proposes a fine-grained parallelization of the Genetic Programming paradigm (GP) using the Evolvable Agent model (EvAg). The algorithm is decentralized in order to take full-advantage of a massively parallel Peer-to-Peer infrastructure. In this context, GP is particularly demanding due to its high requirements of computational power. To assess the viability of the approach, the EvAg model has been empirically analyzed in a simulated Peer-to-Peer environment where experiments were conducted on two well-known GP problems. Results show that the spatially structured nature of the algorithm is able to yield a good quality in the solutions. Additionally, parallelization improves times to solution by several orders of magnitude.