Title
Machine Learning For Evolution Strategies (Studies In Big Data, 20),Used
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This Book Introduces Numerous Algorithmic Hybridizations Between Both Worlds That Show How Machine Learning Can Improve And Support Evolution Strategies. The Set Of Methods Comprises Covariance Matrix Estimation, Metamodeling Of Fitness And Constraint Functions, Dimensionality Reduction For Search And Visualization Of Highdimensional Optimization Processes, And Clusteringbased Niching. After Giving An Introduction To Evolution Strategies And Machine Learning, The Book Builds The Bridge Between Both Worlds With An Algorithmic And Experimental Perspective. Experiments Mostly Employ A (1+1)Es And Are Implemented In Python Using The Machine Learning Library Scikitlearn. The Examples Are Conducted On Typical Benchmark Problems Illustrating Algorithmic Concepts And Their Experimental Behavior. The Book Closes With A Discussion Of Related Lines Of Research.
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