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Contemporary Evolution Strategies

Author: Thomas Bäck; Christophe Foussette; Peter Krause
Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Series: Natural Computing Series.
Edition/Format:   Print book : Document   Computer File : English
Database:WorldCat
Summary:
Evolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for strategy parameter adaptation. Most importantly, the covariance matrix adaptation strategy (CMA-ES) and its successors are the key  Read more...
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Genre/Form: Electronic books
Material Type: Document
Document Type: Book, Computer File
All Authors / Contributors: Thomas Bäck; Christophe Foussette; Peter Krause
ISBN: 3642401368 9783642401367
OCLC Number: 990529364
Language Note: English.
Notes: Description based upon print version of record.
Description: 1 online resource (101 p.)
Contents: ""Contents""; ""List of Figures""; ""List of Algorithms""; ""Chapter 1 Introduction""; ""1.1 Background and Motivation""; ""1.2 Structure of the Book""; ""1.3 Notation""; ""1.4 Source Code""; ""Chapter 2 Evolution Strategies""; ""2.1 Introduction""; ""2.1.1 Optimization""; ""2.1.2 Evolution Strategies as a Specialization of Evolutionary Algorithms""; ""2.1.3 Mutation in Rn""; ""2.1.3.1 The Multivariate Normal Distribution""; ""2.1.3.2 Relationship Between Covariance Matrix and Hessian""; ""2.2 Algorithms""; ""2.2.1 From the (1+1)-ES to the CMA-ES""; ""2.2.1.1 (1+1)-ES"" ""2.2.1.2 (Î?,λ)-MSC-ES""""2.2.1.3 DR1""; ""2.2.1.4 DR2""; ""2.2.1.5 DR3""; ""2.2.2 Modern Evolution Strategies""; ""2.2.2.1 (Î?W,λ)-CMA-ES""; ""2.2.2.2 LS-CMA-ES""; ""2.2.2.3 LR-CMA-ES""; ""2.2.2.4 IPOP-CMA-ES""; ""2.2.2.5 (1+1)-Cholesky-CMA-ES""; ""2.2.2.6 Active-CMA-ES""; ""2.2.2.7 (Î?,λ)-CMSA-ES""; ""2.2.2.8 sep-CMA-ES""; ""2.2.2.9 (1 + , λsm)-ES""; ""2.2.2.10 xNES""; ""2.2.2.11 (1+1)-Active-CMA-ES""; ""2.2.2.12 (Î?/ Î?W , λiid + λm)-ES""; ""2.2.2.13 SPO-CMA-ES""; ""2.3 Further Aspects of ES""; ""2.3.1 Constraint Handling""; ""2.3.2 Beyond Real-Valued Search Spaces"" ""2.3.3 Multiobjective Optimization""""Chapter 3 Taxonomy of Evolution Strategies""; ""3.1 Development Strands of Modern Evolution Strategies""; ""3.1.1 Overview""; ""3.1.2 Restart Heuristics""; ""3.1.3 Methods for Adapting Mutation Parameters""; ""3.1.4 Methods for Avoiding Function Evaluations""; ""3.2 Characteristics of Modern Evolution Strategies""; ""3.2.1 Computational Effort""; ""3.2.2 Convergence Behavior""; ""3.3 Recommendations for Practical Use""; ""3.3.1 Global Optimization""; ""3.3.2 High-Dimensional Search Spaces""; ""Chapter 4 Empirical Analysis""; ""4.1 Measuring Efficiency"" ""4.1.1 The FCE Measure""""4.1.2 The ERT Measure""; ""4.2 Experiments""; ""4.2.1 Selection of Algorithms""; ""4.2.2 Technical Aspects""; ""4.2.2.1 Framework""; ""4.2.2.2 Software for ES Algorithms""; ""4.2.3 Analysis""; ""4.2.3.1 Calculating FCE from Empirical Results""; ""4.2.3.2 Calculating Rankings""; ""4.2.3.3 Selection of Test Functions""; ""4.2.3.4 Choice of Target Costs Ct""; ""4.3 Results""; ""4.3.1 Ranks by FCE""; ""4.3.2 Discussion of Results""; ""4.4 Further Analysis for n=100""; ""Chapter 5 Summary""; ""Bibliography""
Series Title: Natural Computing Series.
Other Titles: Natural Computing Series

Abstract:

Evolution strategies have more than 50 years of history in the field of evolutionary computation. Since the early 1990s, many algorithmic variations of evolution strategies have been developed, characterized by the fact that they use the so-called derandomization concept for strategy parameter adaptation. Most importantly, the covariance matrix adaptation strategy (CMA-ES) and its successors are the key representatives of this group of contemporary evolution strategies. This book provides an overview of the key algorithm developments between 1990 and 2012, including brief descriptions of the a.

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