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Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels.

, , и . EvoApplications, том 11454 из Lecture Notes in Computer Science, стр. 504-519. Springer, (2019)

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Jörg Stork

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CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems., , , , , , и . CoRR, (2020)Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels., , и . EvoApplications, том 11454 из Lecture Notes in Computer Science, стр. 504-519. Springer, (2019)Tutorials at PPSN 2016., , , , , , , , , и 19 other автор(ы). PPSN, том 9921 из Lecture Notes in Computer Science, стр. 1012-1022. Springer, (2016)Behavior-based neuroevolutionary training in reinforcement learning., , , , , и . GECCO Companion, стр. 1753-1761. ACM, (2021)Prediction of neural network performance by phenotypic modeling., , , и . GECCO (Companion), стр. 1576-1582. ACM, (2019)Understanding the Behavior of Reinforcement Learning Agents., , , и . BIOMA, том 12438 из Lecture Notes in Computer Science, стр. 148-160. Springer, (2020)SVM Ensembles Are Better When Different Kernel Types Are Combined., , , и . ECDA, стр. 191-201. Springer, (2013)Surrogate models for enhancing the efficiency of neuroevolution in reinforcement learning., , , и . GECCO, стр. 934-942. ACM, (2019)Underwater Acoustic Networks for Security Risk Assessment in Public Drinking Water Reservoirs., , , , , , , , , и 1 other автор(ы). CoRR, (2021)Surrogates for hierarchical search spaces: the wedge-kernel and an automated analysis., , , и . GECCO, стр. 916-924. ACM, (2019)