Introduction to Evolutionary Computing (Natural Computing Series) [Hardcover]

Agoston E. Eiben (Author), J.E. Smith (Author)

Book Description

ISBN-10: 3540401849 | ISBN-13: 978-3540401841 | Publication Date: October 7, 2008

The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Editorial Reviews

Review

From the reviews: "This is intended primarily as a textbook for lecturers and graduate and undergraduate students but will certainly attract a wider readership. The authors explain that each of them has many years of teaching experience, and has given instruction on Evolutionary Computing (EC) … and they realised the need for a suitable textbook and decided to write this one. … Beside serving as an introduction the book is a guide to the state-of-the art. … This is a well-produced and very useful book." (Alex M. Andrew, Robotica, Vol. 22, 2004)

About the Author

A.E. Eiben (M.Sc in Maths 1985, Ph.D. in computer science 1991) is one of the European early birds of EC, his first EC paper is dating back to 1989. This was a technical report on Markov chain convergence properties of GAs, that was published in the proceedings of the first European EC conference, the PPSN 1990. Ever since he has been active in the field with special interest in multi-parent recombination, constraint satisfaction, and self-calibrating evolutionary algorithms. During the last decade he was chair or member of the organizing committee of almost all major events of the field: CEC, EP, FOGA, GECCO, PPSN and is a member of the PPSN Steering Committee. Currently he is an editorial board member of premium EC and EC-related jorunals: Evolutionary Computing, Genetic Programming and Evolvable Machines, IEEE Transactions on Evolutionary Computation, Applied Soft Computing, and Natural Computing. Furthermore, he is one of the founders and the executive board members of the European Network of Excellence in Evolutionary Computing, EvoNet. He is one of the series editors of the Springer book series Natural Computing. His also has almost ten years of teaching experience, having given academic and industrial EC courses and organising European EC Summer Schools. J.E. Smith (Msc. Communicating Computer Systems 1993, PhD in computer science 1998) has been actively researching and publishing on the field of EC since 1994. His work has combined theoretical modelling with empirical studies in a number of areas, especially concerning so-called "self-adaptive" and "hybrid" systems which exhibit the common characteristic of being able to "learn how to learn". This research has been backed up with industrial collaborations applying EC-based (and other) techniques to a range of diverse problems such as VLSI verification and bio-informatics. For a number of years he has served on the programme committees of all of the major (and many smaller) conferences in the field, and as a reviewer for all of the principal journals. Since 2000 he has been one of the co-organisers of the annual International Workshop on Memetic Algorithms (WOMA). In addition to teaching courses in Evolutionary Computing in academia and industry, he has been a member of the Training Committee of the European Network of Excellence in Evolutionary Computing, EvoNet, since its formation and as such has been heavily involved in the production of a variety of different training materials for the EvoNet "flying circus".

Product Details

• Hardcover: 316 pages
• Publisher: Springer (October 7, 2008)
• Language: English
• ISBN-10: 3540401849
• ISBN-13: 978-3540401841
• Product Dimensions: 9.4 x 6.3 x 0.9 inches
• Shipping Weight: 1.3 pounds (View shipping rates and policies)
• Average Customer Review: 4.6 out of 5 stars  See all reviews (7 customer reviews)
• Amazon Best Sellers Rank: #107,025 in Books (See Top 100 in Books)
  • #3 in Books > Computers & Technology > Programming > Algorithms > Genetic
  • #8 in Books > Computers & Technology > Computer Science > Artificial Intelligence > Computer Mathematics

Customer Reviews

Most Helpful Customer Reviews

24 of 25 people found the following review helpful:

5.0 out of 5 stars Excellent introduction, February 1, 2005

By 

meerkat "Captain Meerkat" (Moscow, ID USA) - See all my reviews

This review is from: Introduction to Evolutionary Computing (Natural Computing Series) (Hardcover)

I taught our introduction to evolutionary computation class from this book. It is a well rounded introduction to the topic covering most of the introductorty material you would expect. There is an real dearth of good introductory books for EC. This is probably the best because of its breadth. Its weakness is its lack of detail. It would not hurt if they covered the same material in about 50% more pages. As soon as they start a topic its over and on to the next topic. But if you are new to the field they give plenty of references and touch on most topics in enough detail for students to implement. All in all a good solid job.

18 of 19 people found the following review helpful:

4.0 out of 5 stars Evolution as a practical tool, April 3, 2006

By 

W Boudville (Terra, Sol 3) - See all my reviews
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This review is from: Introduction to Evolutionary Computing (Natural Computing Series) (Hardcover)

The authors emphasise from the get-go that this book is meant as a practical introduction to the application of evolutionary computing. It is not a high brow, abstruse monograph. (Which indeed Springer texts often are.)

The level of discussion can be adequately understood by someone with a good background in computing and hopefully also in some science or engineering field. Certainly, there are important abstractions that must be mastered. Like how the evolutionary search can be seen as a path across a fitness landscape or potential energy surface. But there appears to be a careful explanation of the minimum necessary maths to convey an idea. And where a chapter's references might point to more specialised texts or journal papers that give a fuller math treatment.

It may well be, as another reviewer remarked, that there is insufficient detail in some passages of this book. But perhaps the text is not meant to be a low level "user's manual" type of discussion.

If you do find this book useful, consider a more advanced text, "Foundations of Genetic Programming" by Langdon and Poli, also published by Springer. It takes you deeper into the subject.

9 of 9 people found the following review helpful:

5.0 out of 5 stars good textbook, October 30, 2006

By 

I. Tagkopoulos (Princeton,NJ) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Evolutionary Computing (Natural Computing Series) (Hardcover)

I have used evolutionary programming in my research in the past and have read several books on the topic. This is one of the most well written books available, that can easily be read by a beginner despite its depth. The conclusions that they draw are logical and supported by the appropriate references (I was not impressed with the theory and results in the field, but this has nothing to do with the quality of this book).