Titlebook: General-Purpose Optimization Through Information Maximization; Alan J. Lockett Book 2020 Springer-Verlag GmbH Germany, part of Springer Na

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Review of Optimization Methods,computer, however, analytic solutions and fast-converging iterative methods were the only practical means of performing optimization. The introduction and proliferation of computing technologies widened both the scope and the number of optimization problems.

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Performance Experiments,ese performance criteria on a bank of standard optimizers and objectives. The complete results are provided for reference in tabular form in Appendix A. They are summarized and discussed below. In addition, the theoretical continuity of performance criteria is illustrated through several examples

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The Information Maximization Principle,n-. fitnesses can be exploited to optimize over search methods. First, we introduce fitness measures with some degree of predictability, emphasizing that such fitness measures can cover a wide range of settings for search and optimization.

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https://doi.org/10.1007/978-3-662-62007-6Artificial Intelligence; Neuroevolution; Information Maximization; Optimization; Evolutionary Annealing;

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Computer Networks / Computernetzeverning those decisions will result in correspondingly small changes to the iterates of the process. The search generators introduced in Definition 4.6 represent how an iterative search process chooses the next point stochastically based on the prior search history. The concept that there can be arb