Abstract
We describe a new Genetic Programming systemnamed EC-Star. It is supported by an open infrastructure, commercial-volunteer-client parallelization framework. The framework enables robust and massive-scale evolution and motivates the hub and spoke network topology of EC-Star’s distributed GP model. In this model an Evolution Coordinator occupies the hub and an Evolutionary Engine occupies each spoke. The Evolution Coordinator uses a layered framework to dispatch high performing, partially evaluated candidate solutions for additional fitness-case exposure, genetic mixing, and evolution to its Evolutionary Engines. It operates asynchronously with each Evolutionary Engine and never blocks waiting for results from an Evolutionary Engine.
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Notes
- 1.
The compute resource is commercial-volunteer in the sense that it is doing work on behalf of someone else, but is being paid to do it.
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Acknowledgements
The authors acknowledge the generous support of the Li Ka Shing Foundation as well as Kaivan Kamali and Hormoz Shahrzad of Genetic Finance and Kalyan Veeramachaneni of MIT.
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O’Reilly, UM., Wagy, M., Hodjat, B. (2013). EC-Star: A Massive-Scale, Hub and Spoke, Distributed Genetic Programming System. In: Riolo, R., Vladislavleva, E., Ritchie, M., Moore, J. (eds) Genetic Programming Theory and Practice X. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6846-2_6
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