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

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CCU Predictive Instrument (CCU)Euclidean space to demonstrate that an information maximizing approach to optimization is both feasible and effective. An important feature of evolutionary annealing is that it can be applied to any measurable space.

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The Evolutionary Annealing Method,In Chapter 13, an optimization method was shown to achieve its best performance on a given problem by making full use of the information about the objective function obtained from function evaluations, and martingale optimizers were proposed as a consequence.

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Evolutionary Annealing in Euclidean Space,Evolutionary annealing was developed in the last chapter as a general-purpose optimization technique. This chapter presents an application of evolutionary annealing to the space of finite real vectors. Experiments are performed to compare real-space evolutionary annealing (REA) on the set of benchmarks and algorithms from Chapter 11.

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Computer Networks and the Internetn methods may outperform the methods being interpolated. These facts are demonstrated experimentally in Chapter 11. Further, the categories of performance criteria described in this chapter make it possible to identify the conditions under which No Free Lunch theorems hold in infinite-dimensional spaces, to be undertaken in Chapter 12.

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