Fresh back from GECCO 2017, which is probably the main event for evolutionary algorithms and other metaheuristics. Together with the conference proper, there are workshops and tutorials. Last year we achieved full score, with papers, posters and tutorials. Unfortunately, not this year.
We’re happy though with the two papers that were accepted in the EvoSoft workshop, which we usually attend, and the BBOB benchmarking workshop. Both used the same thing, EvospaceJS, Mario’s framework for working with tuple-space pool-based evolutionary algorithms. The idea of this pool is decoupling algorithms from population. And as soon as you do that, a world of posibility opens, like using different clients on the same pool. In the EvoSoft paper, evospace-js: asynchronous pool-based execution of heterogeneous metaheuristics, we presented the general framework and a pool of concept which combined PSO and evolutionary algorithms, with very interesting results. Here’s the rather laconic presentation, which is a reason more to check out the paper.
In the second paperBenchmarking a pool-based execution with GA and PSO workers on the BBOB noiseless testbed.
All in all, EvospaceJS and NodIO, the two frameworks we work with, offer a nice platform for experimentation with different kind of algorithms that can be easily transported to the cloud and adapted to volunteer computing environments. Whatever the case, it also has an interesting dynamics that has an influence on the working of the evolutionary algorithms. Sure, we will continue tapping this source of interesting insights on evolutionary models.
Asynchronous, heterogeneous, pool based evolutionary algorithms in GECCO 2017
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