Cantitate/Preț
Produs
Total produse
Vezi coșul
The Theory of Evolution Strategies de Hans-Georg Beyer

The Theory of Evolution Strategies: Natural Computing Series

Autor Hans-Georg Beyer
en Limba Engleză Hardback – 27 mar 2001
Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much.
This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 99226 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 6 dec 2010 99226 lei  6-8 săpt.
Hardback (1) 99756 lei  6-8 săpt.
  Springer Berlin, Heidelberg – 27 mar 2001 99756 lei  6-8 săpt.

Din seria Natural Computing Series

Preț: 99756 lei

Preț vechi: 124695 lei
-20% Nou

Puncte Express: 1496
Preț estimativ în valută:
19088€ • 19983$ • 15794£

Carte tipărită la comandă

Livrare economică 05-19 aprilie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783540672975
ISBN-10: 3540672974
Pagini: 406
Ilustrații: XX, 381 p.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.71 kg
Ediția:2001
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Natural Computing Series

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

1. Introduction.- 2. Concepts for the Analysis of the ES.- 3. The Progress Rate of the (1 % MathType!MTEF!2!1!+-% feaagCart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8% qadaqadaWdaeaapeGaaGyma8aadaWfGaqaa8qacaGGSaaal8aabeqa% a8qacqGHRaWkaaGccqaH7oaBaiaawIcacaGLPaaaaaa!3C4E!$$\left( {1\mathop ,\limits^ + \lambda } \right)$$ ?)-ES on the Sphere Model.- 5. The Analysis of the (?, ?)-ES.- 6. The (?/?, ?) Strategies — or Why “Sex” May be Good.- 7. The (1, ?)-?-Self-Adaptation.- Appendices.- A. Integrals.- A.1 Definite Integrals of the Normal Distribution.- A.2 Indefinite Integrals of the Normal Distribution.- A.3 Some Integral Identities.- B. Approximations.- B.1 Frequently Used Taylor Expansions.- B.3 Cumulants, Moments, and Approximations.- B.3.1 Fundamental Relations.- B.3.2 The Weight Coefficients for the Density Approximation of a Standardized Random Variable.- B.4 Approximation of the Quantile Function.- C. The Normal Distribution.- C.3 Product Moments of Correlated Gaussian Mutations.- C.3.1 Fundamental Relations.- C.3.2 Derivation of the Product Moments.- D. (1, ?)-Progress Coefficients.- D.2 Table of Progress Coefficients of the (1, ?)-ES.- References.

Recenzii

From the reviews:
"He gives an extensive mathematical treatment of idealised models of behaviour for several types of EA … . The detail is extensive enough to guide and educate graduate students … . The figures are clear and convincing. Part of the quality of the book is its aesthetically pleasing layout, for both figures and mathematics. … The book is a desirable resource for all those, students and others, who need or wish to have a single portable source for the mathematically-based fundamentals of the subject." (John Campbell, Expert Update, Vol. 6 (1), 2003)
"Evolutionary algorithms (EA) have found a broad acceptance as robust optimization algorithms in the last ten years. … The aim of this monograph is to provide a theoretical framework for the ES research field. … The book contains references to open problems, to new problem formulations, and to future research directions at the relevant places." (Horst Hollatz, Zentralblatt MATH, Vol. 969, 2001)

Textul de pe ultima copertă

Evolutionary Algorithms, in particular Evolution Strategies, Genetic Algorithms, or Evolutionary Programming, have found wide acceptance as robust optimization algorithms in the last ten years. Compared with the broad propagation and the resulting practical prosperity in different scientific fields, the theory has not progressed as much.
This monograph provides the framework and the first steps toward the theoretical analysis of Evolution Strategies (ES). The main emphasis is on understanding the functioning of these probabilistic optimization algorithms in real-valued search spaces by investigating the dynamical properties of some well-established ES algorithms. The book introduces the basic concepts of this analysis, such as progress rate, quality gain, and self-adaptation response, and describes how to calculate these quantities. Based on the analysis, functioning principles are derived, aiming at a qualitative understanding of why and how ES algorithms work.

Caracteristici

Provides the theoretical framework for Evolution Strategies Includes supplementary material: sn.pub/extras