Sergey Grabkovsky

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Neuroevolution is a useful machine learning approach for problems with limited domain knowledge, but it has not done well with strategic decision-making problems, where the correct action varies sharply as the agent moves across states. Two promising neuroevolution algorithms are Neuro Evolution of Augmenting Topologies (NEAT) and its extension, Hyper NEAT.(More)
Neuroevolution is a useful machine learning approach for problems with limited domain knowledge, but it has not done well with strategic decision-making problems, where the correct action varies sharply as the agent moves across states. Two promising neuroevolution algorithms are NeuroEvolution of Augmenting Topologies (NEAT) and its extension, HyperNEAT.(More)
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