Newsletter   Secure Checkout   View Cart (0 items)  
Search:    Welcome Guest! Save up to 30-40% on most items with our awesome everyday discounts!

Theory of Evolution Strategies [Hardcover]

Our Price $ 168.26  
Retail Value $ 179.00  
You Save $ 10.74  
Item Number 226366  
Buy New $168.26
Available on the Internet only.

Item description for Theory of Evolution Strategies by Hans-Georg Beyer...

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.

Promise Angels is dedicated to bringing you great books at great prices. Whether you read for entertainment, to learn, or for literacy - you will find what you want at!

Item Specifications...

Pages   380
Est. Packaging Dimensions:   Length: 9.44" Width: 6.42" Height: 1.1"
Weight:   1.71 lbs.
Binding  Hardcover
Release Date   Apr 27, 2001
Publisher   Springer
ISBN  3540672974  
ISBN13  9783540672975  

Availability  79 units.
Availability accurate as of May 25, 2017 01:30.
Usually ships within one to two business days from La Vergne, TN.
Orders shipping to an address other than a confirmed Credit Card / Paypal Billing address may incur and additional processing delay.

More About Hans-Georg Beyer

Register your artisan biography and upload your photo! Hans-Georg Beyer was born in 1959.

Are You The Artisan or Author behind this product?
Improve our customers experience by registering for an Artisan Biography Center Homepage.

Product Categories

1Books > Bargain Books > Children > Science, Nature & How It Works
2Books > Bargain Books > Science & Nature
3Books > Special Features > New & Used Textbooks > Computer Science & Information Systems > Artificial Intelligence
4Books > Special Features > New & Used Textbooks > Computer Science & Information Systems > Programming Languages
5Books > Special Features > New & Used Textbooks > Sciences > Mathematics
6Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Computer Mathematics
7Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > General
8Books > Subjects > Computers & Internet > Computer Science > Artificial Intelligence > Theory of Computing
9Books > Subjects > Computers & Internet > General
10Books > Subjects > Computers & Internet > Programming > Algorithms > General
11Books > Subjects > Computers & Internet > Programming > Algorithms > Genetic
12Books > Subjects > Computers & Internet > Programming > General
13Books > Subjects > Professional & Technical > Professional Science > Mathematics > Applied > Linear Programming
14Books > Subjects > Science > Biological Sciences > Bioinformatics
15Books > Subjects > Science > Evolution > General
16Books > Subjects > Science > General
17Books > Subjects > Science > Mathematics > Applied > Linear Programming
18Books > Subjects > Science > Mathematics > General

Reviews - What do customers think about Theory of Evolution Strategies?

The German Tradition  Aug 21, 2005
This monograph is a detailed treatment of a strain of evolutionary computing called "evolution strategies" (ES), which comes out of Germany and follows from the work of Ingo Rechenberg, Hans-Paul Schwefel, Günter Rudolph, Beyer, and a few others. It is distinct from Goldberg's genetic algorithms (GA), Fogel's evolutionary programming (EP), Koza's genetic programming (GP), and simulated annealing.

It is quite a dense book, making heavy use of differential geometry. You can find a more brief treatment of ES along with a comparison to EP and GA in Bäck's "Evolutionary Algorithms in Theory and Practice".
The first of its kind  Sep 11, 2001
This is the first book that I am aware of that addresses the foundations of evolutionary and genetic algorithms, evolution strategies, and evolutionary programming from a rigorous mathematical point of view. The book is designed for an audience of mathematicians and computer scientists who are curious about evolutionary strategies and need a formal treatment of its foundations. Readers currently involved in designing and writing genetic programs will find this book helpful in the optimizing of their algorithms, even though at times they might find the presentation a little heavy-handed.

Evolutionary strategies are thought of as dynamical systems in the book, but these are not in general deterministic, but probabilistic in nature. The state space of the dynamical system consists of the direct product of an object parameter space, an endogenous strategy parameter set, and a collection of fitness functions. Evolution takes place in this state space via the "genetic operators", i.e. the selection, mutation, reproduction, and recombination operators. The goal of course is to find an optimum solution to the problem, and so a consideration of the convergence of the evolution strategy to this optimum must be addressed.

These issues and others, such as the differentiation between evolutionary strategies and ordinary Monte Carlo methods, are discussed in great detail in the book. The author emphasizes that the mechanism of evolutionary strategies lies in the local properties of state space, the evolutionary process being obtained by small steps in this space. He also suggests three prerequisites for the working of evolutionary algorithms, namely the evolutionary progress principle, the genetic repair hypothesis, and mutation-induced operation by recombination. The first is the statement that each change of the individuals in the state space can result in fitness gain as well as fitness loss. The second is a device employed for statistical estimation, and attempts to answer why recombinant evolution strategies are better than nonrecombinant strategies. The third is the statement that dominant recombination causes cohesion of a population and is represented by a local operator which transforms the mutations by a random sampling process.

The author makes use of differential geometry in the book to establish a theoretical framework to predict the local performance of evolution strategies. The hypersurface model is constructed as a fitness model for the calculation of progress measures, and for an elementary model of evolution dynamics. Tensor calculus is employed to study deformations of the sphere model, with the goal of obtaining useful formulae for the progress rate. A mean radius of this deformation is calculated, to serve as a substitute radius in the progress rate formulae for the sphere model.

For the case of (1+1)-selection, i.e. one parent and one offspring, where both parents and offspring are contained in the selection pool, the author derives exact integral representations for the progress rate. The quality gain for one parent and any member of offspring is also considered, and the author derives an integral expression for it using an approximation of the distribution function of the mutation-induced fitness distribution. He argues that the progress rate and the quality gain are progress measures that describe totally different aspects of the performance of evolution strategies.

The general problem of an evolution strategy with arbitrary numbers of parents and offspring is also considered. Since the distribution of parents in the parameter space is unknow, and since it changes in successive generations, this makes the analysis of the progress rate extremely difficult. The author does however derive the relations for this model in terms of a formal expression for the progress rate which is given as an integral over the distribution of a single descendant, which is generation-dependent and unknown. This distribution is approximated using Hermite polynomials and the determination of this function is then reduced to the finding of a collection of coefficients. These coefficients are functions of moments of the offspring and are estimated by the random selection process of the evolution strategy.

Recombinative evolution strategies are also studied by the author, and two special recombination types considered, namely the intermediate and dominant cases. Intermediate recombination is shown to lead to higher performance compared to nonrecombinativie strategies. The dominant case is shown to lead to mutation-induced speciation by recombination.

The author also analyzes the dynamic adaptation of the mutation strength to the local topology of the fitness landscape. Self-adaptation, which is the method for applying evolution to the adjustment of optimal strategy parameter values, is given detailed treatment for the case of one parent in terms of mean value dynamics.


Write your own review about Theory of Evolution Strategies

Ask A Question or Provide Feedback regarding Theory of Evolution Strategies

Item Feedback and Product Questions
For immediate assistance call 888.395.0572 during the hours of 10am thru 8pm EST Monday thru Friday and a customer care representative will be happy to help you!

Help us continuously improve our service by reporting your feedback or questions below:

I have a question regarding this product
The information above is incorrect or conflicting
The page has misspellings or incorrect grammar
The page did not load correctly in my browser or created an error.

Email Address:
Anti Spam Question. To combat spammers we require that you answer a simple question.
What color is the sky?
Leave This Blank :
Do Not Change This Text :

Add This Product Widget To Your Website

Looking to add this information to your own website? Then use our Product Widget to allow you to display product information in a frame that is 120 pixels wide by 240 pixels high.

    Copy and paste the following HTML into your website and enjoy!

Order toll-free weekdays 10am thru 10pm EST by phone: 1-888-395-0572 (Lines are closed on holidays & weekends.)
Customer Service | My Account | Track My Orders | Return Policy | Request Free Catalog | Email Newsletter

Gift Certificates
RSS Feeds
About Us
Contact Us
Terms Of Use
Privacy Policy