Genetic Algorithms in Search, Optimization, and Machine Learning
by DavidE. Goldberg
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Hardcover (01 January, 1989)
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Editorial Review

David Goldberg's Genetic Algorithms in Search, Optimization and Machine Learning is by far the bestselling introduction to genetic algorithms. Goldberg is one of the preeminent researchers in the field--he has published over 100 research articles on genetic algorithms and is a student of John Holland, the father of genetic algorithms--and his deep understanding of the material shines through. The book contains a complete listing of a simple genetic algorithm in Pascal, which C programmers can easily understand. The book covers all of the important topics in the field, including crossover, mutation, classifier systems, and fitness scaling, giving a novice with a computer science background enough information to implement a genetic algorithm and describe genetic algorithms to a friend. ... Read more

Reviews (16)

Read a review article instead!
I agree with another reviewer who said the book was unnecessarily long.Genetic Algorithms are a great programming tool, and there are some tips and tricks that can help your programs converge faster and more accurately, but this book had a lot of redundant information.

If you are interested in using GA for solution-finding, I doubt you'll find much useful in this book beyond the first chapter or so.Many of the examples later in the book were so specific that I couldn't see how they could be usefully generalized.Really optimizing a GA approach for a specific problem domain takes a fair amount of tuning, and this book won't help much with that.

I think time spent surfing siteseer or other publication sites would be better spent than reading this book.

Needs updating
OK, I agree with the previous reviewers: it's the classical textbook for GAs. But it definitely needs updating, as it's a 15-year old book and much has been done in the area. Niching methods, for example, are just outlined. I'd recommend Melanie Mitchell's book instead of this one.

The Best Book in AI so far
This book got me so excited that I was not able to continue reading. I had to put it down and walk about. The power of the learning classifier system (SCS) has yet to be fully explored. A system that organizes data (classifies) and learns new rules (generate new rules via the genetic algorithm) is a combination that still takes my breath away. The only negative to this book are the trivial problems the algorithms solve. There is none for the "bucket brigade" version of the SCS. Overall though it is an awesome book presenting a very powerful algorithm that has yet to be fully explored. ... Read more

Isbn: 0201157675
Subjects:  1. Artificial Intelligence - General    2. Combinatorics    3. Computer Bks - General Information    4. Computer Books: Operating Systems    5. Discrete Mathematics    6. Genetic algorithms    7. Machine learning    8. Optimization (Mathematical Theory)   

Genetic Programming : An Introduction : On the Automatic Evolution of Computer Programs and Its Applications
by Wolfgang Banzhaf, Peter Nordin, Robert E. Keller, Frank D. Francone
Average Customer Review:
Hardcover (30 November, 1997)
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Editorial Review

Imagine a world in which computers program other computers based on strategies borrowed from biology and natural selection. Genetic Programming: An Introduction explores fascinating possibilities like these in a thriving area of computer-science research. This research-quality book is for anyone who wants to see what genetic programming is and what it can offer the future of computing.

This text begins by situating genetic programming in terms of the history of computing and machine learning. Early sections show the links between Darwinism, molecular biology, and genetic programming. (Genetic programming uses the strategy of natural selection by solving a problem in successive iterations, which produces the "fittest" solution, much like new species evolve in the natural world.)

The authors present a lot of molecular-biology background since it is central to the genetic-programming project. (There are interesting parallels here. Just as our DNA contains inert information, programs developed using genetic algorithms usually contain many "extra" instructions, too--which often leads to bloated, though effective, code in the final product.) Even though this is extremely technical material, the authors do manage to engage the reader in the imaginative leap from Darwin and DNA to computers and the world of genetic programming.

Later chapters define what genetic programming is and what strategies it uses to let computers program themselves. The authors also examine the state of the art of genetic programming and define what problems need to be solved before it can be widely adopted. The amount of research in this section will mostly benefit specialists in the genetic-programming field.

A later chapter on applications that use genetic programming offers dozens of papers, with applications of this approach from a wide variety of fields, including biology, industry, and computers (and some impressive technologies such as robotics and data mining). Though the authors exaggerate somewhat on how "real world" these applications are, it's clear that genetic programming will continue to improve and find its way into more areas of computing--with even more productive results. Though coding by humans is safe for the foreseeable future, genetic programming offers an appealing alternative to some kinds of problems. --Richard V. Dragan ... Read more

Reviews (8)

Good as an overall, not for the details
This book is good for getting a general view of genetic programming. Nevertheless, I think it neglects many details. For example, it is very hard to from the book how a simple selection strategy (tournament selection) works in practice.

I do not think this book is useful for someone intending to code a genetic programming algorithm.

terrific textbook
I skimmed the Koza books (GP: I & II) and this one at the store. Using the layout, chapter names, and the introductory chapters as my guide, I decided to buy this book to introduce me to the current state of the art in GP. The strengths of this book are its textbook format and the informal exercises that are presented for the reader at the end of every chapter. There is also a great deal of compilation from other relevant gp works presented in a localized, intra-chapter basis. The book is thus highly digestable to a newcomer, and is a far less time-consuming way to learn about GP than through the "expert" papers on the web. Having now almost finished the book, I feel that I am ready and able to author and apply GP techniques in a wide variety of applications and languages, having spent less than 20 hours in study time. A terrific achievement by Banzhaf and company, highly recommended.

Excellent, comprehensive and easy to read.
We all know that kind of books where the author likes to show how much he knows making things intentionally complex....well...this is the opposite side of the spectrum.
The book is very complete and detailed yet easy to read, even after a day of work.
The first part of the book contains introductory information on background areas like probability, biology and computer science as a general discipline.
Getting into the topic, it clarifies some of the differences between evolutionary systems and genetic algorithms and shows how all this contributes to the theory of genetic programming and the evolution of computer programs.
It explains how things are done with different types of individuals (tree, linear, graph, etc) and gives valuable insight about the implementation process.
Although you may need other sources for formal treatment of some topics, this book is a very good acquisition. ... Read more

Isbn: 155860510X
Subjects:  1. Artificial Intelligence - General    2. Computer Bks - General Information    3. Computer Books: Languages    4. Computer Graphics - Design    5. Computers    6. Genetic Algorithms    7. Genetic programming (Computer    8. Genetic programming (Computer science)    9. Programming - Software Development    10. Computers / Artificial Intelligence   

The Simple Genetic Algorithm: Foundations and Theory (Complex Adaptive Systems)
by Michael D. Vose
Average Customer Review:
Hardcover (27 August, 1999)
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Editorial Review

It might be simple, but it's not easy. Computer scientist Michael D. Vose takes a rigorous look at The Simple Genetic Algorithm and shows the state of our knowledge in a book appropriate for advanced undergraduates, graduate students, and professionals.

Vose has decided to approach his subject as a mathematical object, keeping his discussion to a minimum and relying on mathematical demonstrations of what has been proven about this powerful genetic search. This approach maximizes the book's utility for its scope of readers; since each chapter builds on the material before, it makes a good teaching tool, but it is still a useful reference as the indexing helps the professional find proofs quickly.

Covering the basics of random heuristic searching and the nature of the algorithm, the book moves on to computing, transient and asymptotic behavior, models, and schemata. Cutting all of the material down to the basic provable theorems is not, as Vose admits, without problems: any speculation beyond these stripped-down proofs is left to the imaginative reader. But the intrepid explorer couldn't ask for firmer ground from which to launch flights of discovery, and genetic computation currently offers the widest frontiers. --Rob Lightner ... Read more

Reviews (5)

one of a kind modern classic
This book is the result of the author's attempts to "really understand" evolutionary algorithms.It's very mathematical and rigorous, though sometimes the formulation is not very usual. ( a warning!)You may need a few references, and pondering.

Is this a perfect book?Maybe not.But it's very important for the deeper understanding of GA...a landmark great job!

All people who are interested in the underpinning of GA should get this book.It's also a good supplement for mathematical modeling in the sense that it presents a very hard topic that few people have tried to formulate.I mean a very good demonstration of modeling complicated structures like heuristic learning process.And also a good supplement of general dynamical systems.

The style is kind of Dirac-like -- few words, short, original but you barely can add more words to the margins.It's a kind of modernized Chinese meal -- less oily, but still nutritious!!I cannot find any annoying and useless aside in the whole book.

The book is beautiful and well-bound, and nice paper, cover, etc.I got the hardback, though.

A mathematical introduction to Genetic Algorithms
This book is for mathematicians or people who want to study genetic algorithms formally. If you are looking for a book that does not emphasize on the mathematical aspects and talks about parallels between genetic algorithms and natural selection,etc., then you should buy the books written by Goldberg or Mitchell.

It is a great introduction to genetic algorithms for advanced undergraduate mathematics students or people with sufficient math knowledge and maturity. If you read it without these prerequisites, you will only be able to understand little bits and will get lost in the formalism.

Prior knowledge of genetic algorithms is recommended. I did not give this book the perfect rating because I find that the author should introduce concepts intuitively before giving their mathematical definitions. I am aware that this can be a consequence of a lack of mathematical maturity on my part. If you are tired of reading books on genetic algorithms that talk about natural selection,etc. but do not formalize the concepts involved, then this a book for you.

A Great Starting Point for GA Research
I was lucky enough to have Dr. Vose for a graduate course in Genetic Algorithms at the University of Tennessee.The course content was very similar to this book, and gave me the knowledge needed to successfully apply GA's to a wide range of real-life problems.Dr. Vose is a gifted mathematician and computer scientist, and I highly recommend this book. ... Read more

Isbn: 026222058X
Subjects:  1. Artificial Intelligence - General    2. Computer Bks - General Information    3. Computer Books: General    4. Computer Science    5. Computers    6. General    7. Genetic Algorithms    8. Programming - General    9. Computers / Computer Science   

Blondie24: Playing at the Edge of AI (The Morgan Kaufmann Series in Evolutionary Computation)
by David B. Fogel
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Paperback (22 September, 2001)
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Editorial Review

What must it do to the human male ego to find out that theyoung woman who just handily won an online game of checkers is actuallya sleek piece of software with no real understanding of the game'srules? Evolutionary programmers David B. Fogel and Kumar Chellapillalearned this and many other lessons in their quest to build aproblem-solver divorced from human expertise. Fogel's bookBlondie24: Playing at the Edge of AI captures their spirit ofgood-natured questioning of the received wisdom of traditional checkersplaying and AI research.

The writing is surprisingly engaging, comingfrom a software researcher; even readers with little interest incheckers will follow Fogel's many game analyses with rising interest ashis neural networks increase in prowess. Ever the scientist, heincludes a laundry list of fairly harsh critiques of his work--withrebuttals--as an appendix. Devotees of cutting-edge AI, onlinepsychology, or tournament-level checkers will find plenty of interestin the exploits of Blondie24. --Rob Lightner ... Read more

Reviews (32)

A True Technology Adventure
I started reading David Fogel's "Blondie24: Playing at the Edge of AI" on a recent flight more or less to better my professional knowledge.I also had a `fun' book.However, once I started reading Blondie24 I could not put it down.It is a true technology adventure that describes the development of an innovative program that teaches itself to play checkers.And it did this with no expert input or help.Rather it just plays a second version of itself.The two versions independently `evolve' to determine winning positions and strategies.As Fogel describes, in short order the program can easily beat its creator.And not long there after 99% of the people participating on a checkers playing website.That's amazing.And I do this sort of stuff for a living.

David Fogel is a world renowned expert and innovator in the development of evolutionary learning techniques described in Blondie24.His work is the state of the art, well known and respected by all in the field.The program and its implications are not only fascinating but extremely important and I believe a real look into the future for the development of `intelligent' systems.

I highly recommend Blondie24 to anyone even mildly interested in current AI technologies and the future of computing and intelligent systems. It's a great book.

A Leap of Insight into Artificial Intelligence.
The "Leap Of Insight"; Perhaps nothing demonstrates high intelligence more than the ability to bring together the elements of a problem into a solution that no one has ever seen before. The leap of insight extends far beyond teaching or learning; it is the essence of intelligence that expands the body of knowledge as a whole.

To be truly intelligent, Artificial Intelligence must demonstrate the ability to see characteristics and features of problem elements that transcends the initial program. In Blondie24, David Fogel and Kumar Chellapilla show through their own leap of insight that evolved neural networks can dramatically exceed the knowledge set embedded by the programmers.

This engaging story of David and Kumar's journey to prove that true Artificial Intelligence is within the art of the possible will entertain and capture the readers' attention, regardless of the readers' knowledge of computer science.

Great Stuff
This book should probably appeal to almost anyone with an interest in artificial intelligence.

For the beginner this book offers a nice intuitive introduction to subject areas such as neural nets and genetic algorithms.

The expert is not likely to learn any technical matertial but will probably enjoy it as it is a wonderfully written story and perhaps some inspiration. If all you want is a technical manual, then you should look elsewhere.

My level of knowledge of AI is closer to a beginner than an expert.Here are three things that struck me:

1.How long it can take to evolve a good solution.One example from the book took 6 months using pentium 400.

2.How petty academics can be.The last section contains comments made by referees reviewing papers written by the author in scientific journals.Most of them smack of "Damn why didn't I think of that.Well since I didn't, I will try to block someone who did".

3.How elegant GA can be.This book has inspired me to seriously study the various techniques in evolutionary methods.

There are two minor annoyances I found in the book.They are both related to the layout of the book.The book is almost square and has relatively short sides.I assume this was done to make the book look like a checkerboard.This gives the book an odd "feel".Because of the dimentions, the amount of material on each page is relatively small and often the diagrams are not on the same page as the words describing them.However these are very minor complaints on what is a very fine book. ... Read more

Isbn: 1558607838
Subjects:  1. Artificial Intelligence    2. Artificial Intelligence - General    3. Computer Bks - General Information    4. Computer checkers    5. Evolutionary computation    6. General    7. Machine learning    8. Science/Mathematics    9. Technology    10. Computers / Artificial Intelligence   

Genetic Algorithms and Engineering Optimization (Engineering Design and Automation)
by MitsuoGen, RunweiCheng
Average Customer Review:
Hardcover (17 December, 1999)
list price: $150.00 -- our price: $137.15
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Reviews (1)

Thorough and well-organized reference
After an introductory review of the literature, Gen and Cheng write a chapter on each class of optimization problems that have been solved with genetic algorithms.Within the chapters they systematically describe eachtechnique that has been used to apply genetic algorithms to the particularproblem.Descriptions include the underlying math and a step-wiseprocedure for implementation.These are backed up with multiple graphs andillustrations, and copious references (737 references in all).A few moreactual examples would have helped, especially in the MultiobjectiveOptimization chapter.The clear organization and number of references makethis an excellent reference for the practitioner, but the level of detailcould make it difficult for someone new to the technique. ... Read more

Isbn: 0471315311
Sales Rank: 222174
Subjects:  1. Artificial Intelligence - General    2. Computer Bks - General Information    3. Engineering - Industrial    4. Genetic Algorithms    5. Industrial Engineering (General)    6. Industrial engineering    7. Life Sciences - Genetics & Genomics    8. Mathematical models    9. Mathematical optimization    10. Science/Mathematics    11. Technology    12. Computer aided manufacture (CAM)    13. Genetic engineering    14. Technology / Engineering / Mechanical   

Genetic Programming: On the Programming of Computers by Means of Natural Selection (Complex Adaptive Systems)
by John R. Koza
Average Customer Review:
Hardcover (11 December, 1992)
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Reviews (6)

The essential reference for GP
Yeah, its a big book...weighs a ton.However, only the first few chapters are concerned with the basic mechanisms of GP (should be familiar to anyone with a background in genetic algorithms or evolutionary computation).The rest of the book is chock full of examples on how to apply GP.These examples are essential and very welcome.I've found that I can usually find a solved problem in Koza that is similar to what I'm after, then I adapt it to my needs.This is a great reference, but don't be fooled into thinking this book is a tutorial.Think of it more as an exposition of GP with examples.For a tutorial, look somewhere else.

Genetic Programming
The book was very large but enjoyable and made the subject very clear and easy to understand.It explained the genetic programming algorithm very well and showed the results of many experiments to show applicability, limitations, and characteristics of the method.

There was some repetition in places, maybe because the author wanted to emphasize some points and also to remain understandable to persons who may read selected chapters or examples rather than from cover to cover, page by page.

Although the book states that Genetic Programming does not depend on the LISP language or features, it uses LISP as its exclusive language of choice.I would like to implement these generally very computationally intensive Genetic Programming Algorithms in a very fast and efficient way, which for me implies assembly language, and although the author gives good tips about making the algorithm run faster the implementation shown is all LISP and nothing else.I am also interested in using the algorithm to generate efficient, parsimonious, code.The author described the additional problems of parsimony, but gave no information on generation of fast code from S expressions.I will have to refer to some compiler books and my own experiments to go further in this area.

I look forward to experimenting with the subject and reading some of Dr. Koza's other books on the subject.

Most fit book?
Genetic algorithms refer to computer programs that 'evolve' in ways similar to biological organisms. 'Natural selection' specifies the features of the solution to look for, strings of binary numbers (or other similar structures) are mated, with the combination of strings containing partial solutions often producing the most 'fit' results. Generation after generation of this process continues towards the 'evolution' of the desired features. Although this reference is quite long, it is quite readable, and can be shortened significantly by omitting a number of subsections as well as chapters not essential to the core concepts, as well as the detailed appendices. This reference shows that a variety of problems from different fields can be solved in terms of a computer program, of which genetic programming can be the means to find one or more such valid computer programs. It is relevant in that genetic programming is another way to effect computation, as well as providing insight with respect to evolution in nature. ... Read more

Isbn: 0262111705
Sales Rank: 227479
Subjects:  1. Artificial Intelligence    2. Artificial Intelligence - General    3. Computer Bks - Other Applications    4. Computer Books: General    5. Computer Science    6. Computers    7. Genetic programming (Computer    8. Genetic programming (Computer science)    9. Miscellaneous Software    10. Reference - General    11. Computers / Computer Science   

Genetic Algorithms + Data Structures = Evolution Programs
by Zbigniew Michalewicz
Average Customer Review:
Hardcover (26 November, 1998)
list price: $59.95 -- our price: $49.63
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Editorial Review

Zbigniew Michalewicz's Genetic Algorithms + Data Structures = Evolution Programs has three sections. The first section is a straightforward introduction to genetic algorithms. In the second section, Michalewicz describes how to apply genetic algorithms to numerical optimization. Michalewicz, who is a pioneer in this field, discusses the rationale for using genetic algorithms for numerical optimization and describes several experiments that show how this new type of genetic algorithm performs. The author devotes the third section of the book to evolution programs. ... Read more

Reviews (9)

could GA get possibly any eaiser to understand???
I saw this book once with one of my buddies,and read the first chapter,,,it was after looking up the first chapter i decided to buy it...I have read some other books on this topic,and since i was kinda in rush for a project which needed GA,i found no other book which explains the concepts and procedures, this straightforward and "right to the point".As far as writing this book goes, "Michalewicz" has done a really really great job.
Go for it guys!!!
cheers,
Amir

One of the best book on genetic algorithms
A very good vision of the evolutionary optimisation techniques not only GA. As well there is an excellent chapter on constraints handling. Maybe it is not one of the easiest book on GA but it is definitely the most useful.

pretty bad
I agree with the previous reviewer: books should be clear and get to the point. Forget about this one. Get Michalewicz and Fogel's "How to solve it" book. It is MUCH better than this one in all levels: it is better written and the content is more authorative and helpful to novices and experts.

This book is supposed to be a textbook. Maybe that's why it sells so well. I guess I am lucky I didn't have to take a class with this thing. ... Read more

Isbn: 3540606769
Subjects:  1. Artificial Intelligence - General    2. Computer Bks - General Information    3. Computer Books: Web Programming    4. Computers    5. Data structures (Computer scie    6. Data structures (Computer science)    7. Discrete Mathematics    8. Evolutionary programming (Comp    9. Evolutionary programming (Computer science)    10. Genetic Algorithms    11. Programming - General    12. Computers / Artificial Intelligence    13. Optimierung    14. Suchalgorithmen    15. optimization    16. probabilistic algorithms    17. probabilistische Algorithmen    18. search techniques