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Applied Intelligence, 1999
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Ohkura, Kazuhiro +2 more
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Ohkura, Kazuhiro +2 more
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2018
Evolution strategies (ESs) are classical variants of evolutionary algorithms which are frequently used to heuristically solve optimization problems, in particular, in continuous domains. In this chapter, a description of classical and contemporary ESs will be provided.
Michael Emmerich, Ofer M. Shir, Hao Wang
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Evolution strategies (ESs) are classical variants of evolutionary algorithms which are frequently used to heuristically solve optimization problems, in particular, in continuous domains. In this chapter, a description of classical and contemporary ESs will be provided.
Michael Emmerich, Ofer M. Shir, Hao Wang
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Evolution and Mixed Strategies
Games and Economic Behavior, 2001Following \textit{J. Maynard Smith} [Evolution and the Theory of Games (1982; Zbl 0526.90102)], the authors investigate evolutionary games of the Hawk-Dove type. \textit{R. Selten} [Theory Decis. Libr., Ser. C2, 67-75 (1980; Zbl 0658.90102)] has shown that evolutionary stable strategies in the asymmetric game are always pure strategies. This could mean
Binmore, Ken, Samuelson, Larry
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Evolution via Strategy Dynamics
Theoretical Population Biology, 1993zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vincent, Thomas L. +2 more
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1997
Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, non-differentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, their primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations.
Yao, X, Liu, Y
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Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, non-differentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, their primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations.
Yao, X, Liu, Y
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Proceedings of the 15th annual conference companion on Genetic and evolutionary computation, 2008
This tutorial gives a basic introduction to evolution strategies, a class of evolutionary algorithms. Key features such as mutation, recombination and selection operators are explained, and specifically the concept of self-adaptation of strategy parameters is introduced.
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This tutorial gives a basic introduction to evolution strategies, a class of evolutionary algorithms. Key features such as mutation, recombination and selection operators are explained, and specifically the concept of self-adaptation of strategy parameters is introduced.
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The evolution of strategy and strategy as evolution
World Futures, 1993Abstract The concept of “strategy” went through a metamorphosic evolution across borders of heritage from its militaristic origin to its development into “strategic management.” Through that evolution, both content and frameworks of strategy changed significantly.
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Evolution strategies – A comprehensive introduction
Natural Computing, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Beyer, Hans-Georg, Schwefel, Hans-Paul
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