The Seamless Peer and Cloud Evolution Framework

Evolutionary algorithms are increasingly being applied to problems that are too computationally expensive to run on a single personal computer due to costly fitness function evaluations and/or large numbers of fitness evaluations. Here, we introduce the Seamless Peer And Cloud Evolution (SPACE) framework, which leverages bleeding edge web technologies to allow the computational resources necessary for running large scale evolutionary experiments to be made available to amateur and professional researchers alike, in a scalable and cost-effective manner, directly from their web browsers. The SPACE framework accomplishes this by distributing fitness evaluations across a heterogeneous pool of cloud compute nodes and peer computers. As a proof of concept, this framework has been attached to the RoboGen open-source platform for the co-evolution of robot bodies and brains, but importantly the framework has been built in a modular fashion such that it can be easily coupled with other evolutionary computation systems.

Published in:
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference - GECCO '16, 821-828
Presented at:
GECCO '16, Denver, Colorado, USA, 20-24 07 2016
New York, New York, USA, ACM Press

 Record created 2016-08-10, last modified 2018-01-28

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