Results 171 to 180 of about 17,365 (211)
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1997
Evolution strategies are a class of general optimisation algorithms which are applicable to functions that are multimodal, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the 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, nondifferentiable, or even discontinuous. Although recombination operators have been introduced into evolution strategies, the primary search operator is still mutation. Classical evolution strategies rely on Gaussian mutations.
Yao, X, Liu, Y
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Evolution strategies – A comprehensive introduction
Natural Computing, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hans-Georg Beyer, Hans-Paul Schwefel
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1976
There is an embarrassing lack of surprises in certain aspects of evolutionary theory. For example, if a bird has only seawater to drink, it is not surprising, given our knowledge of birds in general, that some mechanism must exist for eliminating salt if the bird is to survive.
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There is an embarrassing lack of surprises in certain aspects of evolutionary theory. For example, if a bird has only seawater to drink, it is not surprising, given our knowledge of birds in general, that some mechanism must exist for eliminating salt if the bird is to survive.
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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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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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Introduction to evolution strategies
Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, 2014This 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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Cooperative Strategies and the Evolution of Communication
Artificial Life, 2000Using communication is not the only cooperative strategy that can evolve when organisms need to solve a problem together. This article describes a model that extends MacLennan and Burghardt's [37] synthetic ethology simulation to show that using a spatial world in a simulation allows a wider range of strategies to evolve in response to environmental ...
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A study on combination of differential evolution and evolution strategy
2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012In this paper, a new optimization method based on a combination of Differential Evolution (DE) and Evolution Strategy (ES), which belong to both Meta-Heuristics and Evolutionary Computation, are developed as a fast approximation optimization method. A weak point of DE is weak local search ability and considerable computation time for obtaining a good ...
Keiichiro Yasuda +2 more
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1996
The applications of conventional game theory to economics and decision theory have not been as successful as some of the field’s initiators had hoped for. It was indeed noted by von Neuman and Morgenstern [1] that some of game theory’s most serious limitations were due to its lacking dynamics.
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The applications of conventional game theory to economics and decision theory have not been as successful as some of the field’s initiators had hoped for. It was indeed noted by von Neuman and Morgenstern [1] that some of game theory’s most serious limitations were due to its lacking dynamics.
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Bidirectional Relation between CMA Evolution Strategies and Natural Evolution Strategies
2010This paper investigates the relation between the covariance matrix adaptation evolution strategy and the natural evolution strategy, the latter of which is recently proposed and is formulated as a natural gradient based method on the expected fitness under the mutation distribution.
Youhei Akimoto +3 more
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