Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
23 Breeding Schedules Improve Grid Robot Performance
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As new species arise from biological evolution, new techniques arise when an evolutionary algorithm is used to train virtual robots. This study generalizes the ISAc list encoding for virtual robots working on the Tartarus task and tests a biologically inspired algorithmic technique called hybridization. A collection of 100 populations of virtual robots is trained in three distinct ways. A baseline experiment performs 1000 generations of evolution on each population. Two other collections of runs stop at intermediate points, harvest the currently best controllers from each population, and initialize new runs with the harvested controllers from all of the populations....