Computer Science Books

Beautifully written book covering almost all area of spoken language processing. However, despite of relative ease of reading, it is necessary to warn the beginning reader, that in some sections the deep enough acquaintance to their theme is veiled. It, for example, concerns questions of definition and application of delta function concept in chapter 5 (Digital Signal Processing).

What a wonderful book. Whether you are a computer scientist or mathematician with limited exposure to the discipline of speech processing, or alternatively you are a dedicated expert in this field, you will find everything you are looking for in this book. For two weeks, I couldn't put this thing down. And that's an extraordinary testimony to a book that's 800+ pages of technical detail. If you want a high level understanding of how speech processing works, or if you want to dig in and build your own speech engine, everything you need is right here.

A thourough and complete review about the subject, in which many disciplines (language, computer, probability, statistics, numerical analysis) converge. As a non-practitioner I have found it an enjoyable opportunity to refresh my knowledges in the field of signal processing, and a source of many hints I have been able to develop in other branches. In spite of notations and methodologies (e.g. bayesian) a bit far from I am used to, the near one thousand pages never seemed extreme related to the meaning compressed into them, spreading from base theory to advanced applications.

This book is a comprehensive overview of most of the major topics associated with speech processing. Divided into five main sections, the book is well structured with a clear division of concerns. The title, "Spoken Language Processing", may be misleading to some as language processing topics only accounts for one section of the book.

The first two sections cover the fundamental theories that should be understood before embarking in-depth into a study of speech processing. This may seem an obvious approach but many texts do not follow this pattern making their use as reference tomes limited. Separating background theory from its use is also useful in that it allows a rigorous approach to its description. Too often texts give a hurried imprecise overview of theories used before launching into a long and complex use of the theory; losing the reader instantly in a quagmire of formulae.

The first two sections of the book deals with background material, material that the reader should at least understand the key concepts of. The first section concentrates on speech in general (including production and perception), probability and statistics, and pattern classification. These last two topics mentioned are both important parts of the book and are dealt with in their own chapters. Both are well written with the right amount of explanation and background. Much of the remainder of the book expects at least some familiarity with the material presented here. These chapters, like all chapters in the book finish with a section entitled, "Historical Perspective and Further Reading". The inclusion of recommended further reading, in addition to the vast number of references appearing in each chapter, make the book as a whole a very good starting point for any work in speech processing.

The second section concerns itself with the DSP topics which relate to speech processing. In this section the reader will find everything from FFTs to multi-rate signal processing and speech signal representations to speech coding. Again the section is well written and the reader is not forced to refer to other texts to understand what is written. If a topic is not expanded upon here then it is an indication that is not dealt further in any great depth in the remainder of the book.

The third section of the book covers speech recognition and is probably the section which will find most use with many readers. This section is very thorough in its treatment of the subject. It starts immediately with a discussion of Hidden Markov Models which is almost exclusively the method employed in the pattern matching stage of speech recognition. Any algorithms that are mentioned are also detailed which really make the book useful. In fact algorithms are presented throughout the book making it a practical reference as much as a theoretical one. This is important because there is a big jump from understanding theory to being able to implement an algorithm to exploit that theory. Other topics covered include an excellent chapter on environmental robustness with one of the best discussions of microphones I have seen. Language modelling and search algorithms are given a thorough treatment. I would like to have seen more detailed information on front-end processing and endpoint detection, as this remains a critical stage of the recognition process. Perhaps the level of detail reflects the fact that this is currently a hot research topic with potential for significant advancement.

Section four, on text-to-speech processing, is a good overview of the field and better than any book I've seen on the subject. It shows numerous block diagrams of what you need to build such a system and gives numerous algorithms in pseudocode. It also dedicates a subsection to each block of the text-to-speech system block diagram, discussing in detail what you would need to do to implement that particular block. Since much of the individual blocks have been discussed earlier in the book, it refers you back to specific earlier sections for details.

The fifth section is a short one on entire systems and shows some case studies, concentrating on what Microsoft was doing at the time this book was published, since that is where the authors' research came from. I would highly recommend that anyone anticipating getting into speech processing have a copy of this classic nearby.

This is a great book if you want to know the future of what Microsoft's top researchers like XD Huang etc are thinking and working. Dr Huang is a super star of the field and it is equally worthwhile to read his excellent book.

I loved this book. It covers the history of Open Source and explain WHY people do open source and HOW they make it happen!

The Success of Open Source in a not a just wistful paean to Linux as the title would suggest. Rather, it is two books in one.

The first book is one of the very best recapitulations of the open source movement and all of its predecessors. The second book is about how something that just seemingly shouldn't work, works so well, and how those principles behind its working extend to more than just the open source movement.

The author, a university professor, draws liberally from the traditions of historians, economists, sociologists, and psychologists to paint a compelling picture of why the forces behind open source are not going to go away any time soon. Read in best companion with The Cathedral and the Bazaar, which IS a bit of a wistful paean to Linux, it illuminates its subject wonderfully.

Steven's book brings a rich articulation of the social practices innovations unleashed by the Open Source collective: a new understanding of private property that better fit the tech forces and the challenges of the present. His book it is not a model; it is not the list of the 10 reasons why...; it is not the defense of an emerging theory; but an historical account in which anecdotes, facts, historical moment, tentative hypothesis, set the background to allows the reader to reshape her/his own questions. The book gave me a perspective I have been testing with IT architects, programmers, software designers...I feel myself much more prepare to engage in conversations about the future in a meaningful and effective way. Thanks to the author!

For the serious reader (and who indeed thinks open source is hilarious?), Weber provides a detailed history of how this idea developed. He traces it from the advent of unix in the 1970s, and the generous (ie. low fees) licensing terms by ATT. Which led to the BSD Unix that flourished in the 80s. Also during this time, GNU took off.

But the bulk of the book deals with the 90s onwards. Especially as linux grew from Torvalds' seminal contribution. Its intellectual roots in unix and GNU are studied. We also see the rise of the Free Software Foundation and Apache, as articulate enablers and promoters of open source. All of which was aided by the invention and meteoric growth of the Web. This played a vital role in enabling a global audience of programmers to hear of and contribute their efforts.

I'm a commercial software developer, and found the author's history of the UNIX culture and the story of its evolution into what we now call Open Source to be fascinating. That alone made it a good read for me. Add in the thought provoking analysis of the "whys" (the real point of this book), and it's a killer combo.

Warning: the book is *full* of sentences like "Pluralism at many different levels is being enabled by communications technologies and by experimentation with property; together, these are reducing the marginal cost of adding voices toward an asymptote of zero." Despite that, I've been able to read it at the pace of a thriller, not a textbook.

This is a concise record of Kalman filtering and related estimation methods. It briefly covers both discrete time and continuous estimators and is particularly useful to extend your knowledge of if you are already familiar with some of the material. Also, the appendix has an interesting comparison of the analogous terms and concepts for estimation and control theory. The book makes a breadth of topics accessible to students, practicing engineers and others.

As you can see from the other reviews, Gelb's book is a classic in the Optimal Estimation. I used Gelb to supplement Brown & Hwang's Applied Kalman Filtering text. Brown & Hwang is very readable, written in a conversational tone. It is also *VERY* application focused and has many Matlab examples. However, in their rush to application, I felt Brown & Hwang did not clearly layout the development of the Kalman (it's all there but it is scattered around). On the other hand, Gelb's book is cogent - both clear and concise. I found that Gelb's development and summarization of Kalman and related optimization schemes gave me the foundational understanding to work Brown & Hwang's applicatios.
For this subject, you definitely need probability (thru matrix representation of covariance, means, etc) and stochastic process. Both Gelb and Brown & Hwang review the requisite probability/stochastic processes , but I would recommend a deeper grounding in the subjects (working thru Papoulis, for example).

I worked in the aerospace industry from 1980-1991. During my years at the Aerospace Corporation I got this book as a reference to the application of Kalman filtering to orbit determination and estimation problems. So my experience and appreciation for this book is very similar to my colleagues working nearby me at TRW or Hughes Aircraft and cosequently I am in strong agreement with some of the other amazon reviews of Gelb's book. I always found it to be a key reference for me.

This book should be a great reference for all engineering students who are dealing with dynamic systems, at entry level. Moderate advanced mathematics being involved, the book provides clear and straightforward discussion for a variety of estimation techniques. Moreover, I like the examples contained very much, since they offer you hand-on experience for understanding the techniques better.

I took an estimation class this semester, and the book required was "introduction to Random Signals and Applied Kalman Filtering" by Brown and Hwang. This book was good for those who want to just apply kalman filters, and assumes that you don't care much about the derivations. But it was my first course in estimation, so I needed to get a complete and in depth introduction to the subject. I searched on amazon, and I found this book. I borrowed it from the library, and it was simply great! I like this type of authors that explain all his proofs, and add this one or two lines that make your life easier. Last week, I ordered it from Amazon to add it to my own library. I recommend it to any serious student in estimation or/and control.

Aboujouj83
http://www.qnhl.com

This is an inspriring book. I highly recommend this book for young scientists and anyone who is thinking about a life of research. This should be recommended reading for CS students everywhere.

"The Art of Scientific Innovations" by Professor Syed Ahamed and Dr. Lawrence provides invaluable insights into the great minds and history behind key innovations that continue to greatly impact our lives today. I had the pleasure of meting authors on a number of occasions and have great respect for their vision and dedication to help advance knowledge with a view to improve the quality and well being of our existence as a humanity overall. I can not think of a more inspiring and motivating book than the "The Art of Scientific Innovations" for Doctoral students and alike for whom this book has been dedicated to. Written in a clear and concise manner, the book enables appreciation of the efforts spent in the advancement of science as well as understanding of the characteristics and common threads of great scientific innovations.

I always think that how the artistic ppl think about the things, how they comes up with the new ideas.This is true that the way we looked up the thing is different from the ppl who are scientist.This book help me a lot to improve my creativity skills.

Ideas presented in this book, "The Art of Scientific Innovation: Cases of Classic Creativity", and taught by the author Professor Syed Ahamed in class are proven fruitful for many of his students including myself. The book actually leads "from realization of a concept to the development of a device intended to serve a commercial or social need". It helped a great deal to successfully finish my research on a subject (financial networks), defend my dissertation, implement my ideas in industry and keep working on a patent.
The broad audience of researchers will greatly benefit from this book.

The Art of Scientific Innovation by Professor Syed V Ahamed and Dr Victor Lawrence is a contribution to graduate education not readily found in other scientific text material. What the authors have done is to share their personal experience with guiding Ph.D. students in graduate dissertation work. They elicit the essential ingredients of performing seminal contributions to the field of endeavor. They have created a stream of outstanding flow of scientific creativity by researchers who have made some of the largest contributions to the art of scientific innovation. This report of these contributions combined with their personal analysis of the dissertation process make this a work that should be read by all Ph.D students.

This book is an excellent resource for learning AspectJ. It is perfectly organized to take you from beginner, novice, to expert as you move through each of the chapters, just as you might expect if you were taking a class in AspectJ.

The author's presentation of the material is straightforward and easy to follow, and his examples are not too involved that you lose track of what's going on. Furthermore, the author has an excellent grasp of the language and is really able to show off the power AspectJ has to offer.

What I really appreciate about the book is that he focuses not just on coding, but also on design; I'm a software engineer and am very pleased that the author discusses an aspect as something to be used elegantly, as part of a well-designed system, rather than just another tool that can be abused. He even discusses several new design patterns that AspectJ makes possible.

I truly recommend this book!

I met the author of this book this weekend, and saw him give a presentation on this material. Finally, a book that shows real uses for AOP.
I have been watching AspectJ since I first saw it about a year ago. My first impression was that it was 'cool', but was worried about giving developers more rope with which to hang themselves. Yes, it was cool, but the most practical examples you would see in demos were thing like 'logging'. I was worried that it would just lead more more ways for junior engineers to 'convolute the code', without bringing much benefit for that risk.
The material in this book, ALONG WITH the support the author had from the Eclipse IDE changed my mind. Finally, there were some real examples involving transaction support, JAAS, exception handling, and more. Furthermore, he addressed these topics in the real-world sense of refactoring existing code to prove his points.
If you aren't using an IDE that gives you some support, then I still have my concerns about 'convoluting' your code; but I am more convinced than ever that AOP concepts are worth putting into my mental toolkit. I have no doubt that the way aspects 'inject' behavior into code will reduce our development time, and make our code behave more consistently (no errors because of inconsistencies in the way common things are handled). If you can add one more ball to the things you 'mentally juggle' while developing, add AOP concepts. This book will help.

I have got this book at local Austin Java User Group meeting. First impression: different cover. Most of Manning books are either greenish or almost black-and-white. This one is yellow.

Part 1 provides really good introduction into AOP. This is the first book I have read on AOP; all stuff I have seen before was online or magazine articles. One interesting fact is that this book took a while to consume, compared to the usual two-week cycle I have for technical books. I guess the reason is that the book has more substance than most of the techincal books and Mannigs does not try to pad their books with API references and other stuff that can be easily found online. After the chapter goes through AOP concepts, it explains AspectJ in application to those concepts. Basic syntax as well as some advanced techniques are explained.

Part 2 has examples of basic applications of AspectJ. Of course it starts with the mandatory logging implemented using AOP. Not a very good example in general, since logging is not really a cross-cutting concern, but works for illustration purposes. Other two application areas discussed in this part are implementation policy enforcement and optimization (pooling and caching examples). Policy enorcement part is really interesting, especially if you are into call patterns.

In general, every part follows the same pattern: first the author discusses the conventional approach, then explains challenges of the conventional solution, provides AspectJ-based solution, and gives one or two examples. Very clean language, easy to follow.

Part 3 discusses advanced applications of AspectJ. First it delves into design patterns and idioms of AOP; it's not by any means AspectJ-specific, so would be useful for any AOP implementation. Examples of patterns are providing thread-safe implementations using AspectJ, implementing security (very interesting discussion on JAAS), transaction management, and implementing business rules using AspectJ. The part ends with AspectJ usage in different development phases.

Two appendices: description of AspectJ compiler and Ant integration - only 15 pages for both. Useful as a reference.

Overall impression: an excellent book. Definitely worth reading, even if you are not into AOP yet.

I loved this book, first of all the introduction is the most interesting presentation of AOP that I ever read.

The other chapters are very good too since based on use-cases very easy to reproduce on projects...

A book to have is you want to learn abour AOP (even if not interested by AspectJ per se...)

AspectJ In Action is a great book to use as an introduction to Aspect-oriented Programming. However, AOP is not for developers to whom Java and OO are still new. Without a comfortable understanding of classes, polymorphism, and encapsulation AOP will only further confuse things.

With that said, AspectJ In Action is a wonderful book filled with plenty of examples and explanations about the well-lit areas of AOP as well as many of the dark corners. I enjoyed reading this book because it starts out with the fundamentals and works its way to more and more complex uses of AOP without getting bogged down in language tangents. Also, the direct application of AOP in real Java design areas is very helpful in getting a better feel for when and how AOP can be applied.

I am looking forward to Ramnivas Laddad's next book!

Top Marks for this highly readable and clear intro to Voice over IP. The subject matter is dealt with in reasonable detail and the author achieves great clarity in explaining difficult technical concepts. He also delves a bit into the history and background which also helps to put the subject matter in context. He even adds a small example of how to go about dimensioning a VOIP network at the end of the book.

Aimed specifically at designers of public telecommunications networks, this easy to read book provides practical and useful hands-on information. Where necessary, topics are covered in great detail. For example, 120 pages are dedicated to H.323. Softswitch architecture and programming are covered, and 55 pages are devoted to discussing Quality of Service issues.

We believe this book to be an essential read, and recommend it highly.

Great book on VoIP, still emerging technology. It did a great job in explaining concepts related to QoS such as RSVP, DiffServ and MPLS. Right from basics such as IP, UDP, TCP and various coding techniques you will find great explanation to each and every item. If you are interested in knowing about VoIP or you if u wanna work on VoIP this is the ONLY book you need. There is very detailed and neat explanation related to MGCP, MEGACO, SS7 and SIP too. The only thing that i felt lacking is testing of voice quality both subjective and objective and how they could be done. No doubt in giving 5 *s to it, great job!

This book does a very good job of giving an introduction to the VoIP world. As a professional in the telecom domain, I found this book very useful. Application of VoIP to telco domain as in the case of softswitch architecture for backhaul and the QoS issues that carriers have to deal with is also well covered at a good amount of detail. The book also provides detailed discussion on the protocols. However, I skipped passed these sections and unable to comment if such material was covered well.

Overall - a very good book. Highly recommend it.

I serious think that I should not write this review since I do not understand half of this book, but then again, I have read this and also Cisco Intergrated Voice Data and can in some way be a poor/insufficient abeit enthusastic tour guide. I have noticed other reviewers describing this book as great - but I do not think this book is comparable to monumental classic like Jeff Doyle or Kennedy Clarks books on Routing and Switching - where they display in-depth knowledge on the topic plus an ability to explain thing in the clearest possible way. I rate this book 5 stars for the sole reason that the author do appear to have an overwhelming knowledge of computer telephony - although I cannot quite judge whether they are technically accurate or error free - and has taken his valueable time off to write them down and share with us. While the author definitely has the kindest intention of making it "understanable" to even the not-so-technically-advance group of reader - as is evidenced in the way he start off this book by explaining why bother with IP telephony, and why TCP/IP is inherently unsuitable for IP telephony - I suspect that when it come to harder topics like H.323, SIP etc - there is simply no way or no time to find a more reader friendly way to present it. In the end it is a tough read - so tough that I will have to put it aside for a while as you need to be in the highest state or mental agility and strength to make hard yakka through the book. Nevertheless, this book is a useful reference - and for topics that this author decide not to include - check out Cisco's Integrated Voice and Data.

In writing The Elements of UML Style, Scott Ambler has done the software modeling community a great service. As a consultant and trainer of numerous corporate clients, I see many teams whose individuals understand the semantics of UML, but have yet to gel as a team with common practices and style. On these teams, communication and productivity often suffer when arguments erupt over why something is modeled the way it is and how my way is better. Teams need to agree on a set of common practices and style. The Elements of UML Style is a great starting point.

The Elements of UML Style is small, concise, intuitively organized, and well explained. It proceeds section by section through the various UML diagrams, in the order they are used on a project. These sections provide many tried and true common sense guidelines and some valuable, but less obvious guidelines aimed at creating well-formed models.

Is it necessary? Yes. This is the best compendium of UML modeling guidelines I have seen published. Projects would be foolish to start from scratch.

Is it sufficient? No. It is a starting point. Projects will want to adjust and go beyond what Ambler writes here. For example, The Elements of UML Style provides general guidelines that urge adopting common naming conventions (section 2.3). A corporation or project will want to nail down specific guidelines for their use case, class, and component names. Also, Ambler focuses on the diagrams of UML, but there is more to modeling than the diagrams. UML itself avoids topics such as what constitutes a well-formed use case specification, and so does Ambler's book. One would have to turn to other books or training, such as IconMedialab's Advanced Use Case Lab course for detailed guidelines in these areas.

Will I be an object modeler just by reading this book? No. This is not an intro book to modeling. Read Craig Larman's "Applying UML and Patterns" (for example) to learn how to object model. Instead, The Elements of UML Style brings together many of the nuggets that will help to become a better, more consistent, and easily understood modeler. I will be recommending this book to my clients.

This book has lots of excellent recommendations on style and presentation of UML diagrams. Ambler offers up 236 recommendations to questions such as: How often should I use stereotypes? Should we model keys into our DBMS? Should we require activation boxes on our sequence diagrams?

I have to recommend this little book to anyone beginning to use UML. More experienced object modelers will have developed their own modeling conventions, but they also will benefit from reading Ambler's articulate perspective. He is an accomplished modeler and an effective communicator.

Ambler covers style guidelines for all 9 UML 1.x diagrams. IMHO most of his suggestions are right-on, and his explanations are consise and accessible. I have been modeling OO systems for 10 years, and I don't agree with every recommendation Ambler makes, but I appreciate what he is offering in this book.

I especially like the fact that Ambler included an Appendix that lists all 236 guidelines in just a few pages. The book also has a high-quality bibliography of other modeling resources, and I was quite pleased that this short book also includes an Index for rapid access to terms.

Most development groups endorse the need for programming conventions and consistent naming standards. "The Elements of UML Style" is an extension of this philosophy to UML models, and every project will benefit from the ideas it presents.

There are two people I look to for information about UML: Martin Fowler (noteably: UML Distilled), and Scott Ambler.

With this book all the pieces are there. "UML Distilled" tells us how to use UML, "Agile Modeling" tells us how to use it in an agile way, and now "The Elements of UML Style" tells us how to use it so that the results look good and are understandable.

Physically, it's a nice book. Small and thin, it packs well, and will fit easily into the most overstuffed briefcase or backpack.

The format is good as well. Organized around the different diagrams, with extras for general guidelines and a quick overview of Agile Modeling, it covers related issues together in an easy to digest format. The guidelines themselves are short, concise, and well illustrated with examples.

I found it an easy book to read, being able to pick it up for a few minutes at a time without having to spend a lot of time to regain my context.

No matter how much you model, or what tools you use to do it, this little book will help make your diagrams better.

This is a great reference book for anyone wanting to improve their UML modeling skills. It won't teach you how to model, but it will teach you how to create UML diagrams which are much easier to read and to understand. Although Ambler preaches that "content is more important than representation", the reality is that if your diagrams look like crap then people think that your work is crap. This book describes a collection of very simple techniques, many of which could be considered modeling patterns, for making your UML diagrams look good.

The book contains both modeling tool diagrams and sketches, showing how you'd apply the various techniques with both your users at a whiteboard or developers at a workstation. The sketches are easy to read, which is pretty amazing considering the book is the size of paperback.

The second chapter is almost worth the price of the book itself because it overviews guidelines which could be used on any type of diagram, UML or not. Chapters 4, 5, and 10 are must reads for business analysts because they cover techniques to improve use case diagrams, class diagrams, and activity diagrams, the things you're most likely to show your end users. Making your diagrams understandable is an important step to communicating what you're doing, and maybe even getting funding for your project.

Other chapters focus on guidelines for technical diagrams. Modeling tool vendors should pick this book up and automate these guidelines. If they were to do that they would really improve the quality of their tools.

If you're serious about UML modeling, then this is a must have book. It's so cheap your company should even consider getting a copy for each analyst, architect, and designer that you have on staff.

I still remember the first time I read something written by Scott Ambler. It was an article about 9 years ago in Software Development magazine (actually it was probably the forerunner) about use cases. His style of writing is, was, and always will be so easy to read and comprehend. Perhaps that is why so many folks write to agree and/or disagree with his ideas: there's no AMBIguity there.

Scott's subscribes to and adheres to the KISS principle (Keep It Simple, Scott!). That is what makes it easy to understand and appreciate. In this book Scott has very capably tackled the easily misunderstood (and therefore often misapplied) ideas of the Unified Modeling Language (UML) and presented them in a manner than anyone can understand and apply in their work.

This book is small enough to fit in your pocket but is incredibly massive in applicability. It belongs on the desks of every developer (AND their manager!) working with UML. Whether applying UML in an XP environment or within the constraints of behemoth software development projects, a basic understanding of the UML is essential. This book will get your team there, quickly.

Research shows that the number one factor that contributes to project success (or failure) is the ability (or inability) to communicate well. That was one of the goals of the UML, a truly UNIFIED language in the arena of modeling. A key value in Agile Modeling (AM) is communication. Coupled with the AM principle of Know Your Models and the AM practice of Apply Modeling Standards, this book will assure that your project's modeling efforts shine.

This is a book with a strong focus on modern telecom networks. It has helped me achieve a good understanding of SS 7 - both the protocols and the network aspects. And herein lies the strength of the book - its stress on both the 'academic' and the 'practical'. I would recommned this book to all those who wish to obtain technical insight about mobile, ISDN and Intelligent networks - as SS 7 is at the core of all three. practical aspects.

This book covers all standards used in the world in a very complete way. It describes all aspects of the digital technologies used in the telephony world. I have used it several times in the last weeks, while making some avaliation tests in ISUP and DSS1 and it was very useful!

A text that builds up the subject step by step. Of particular merit is the tutorials on all three subjects - SS7, ISDN and Synchronization. The main theme is rightly SS7 considering its significance in modern telecom networks. A good text both for students and professionals. More details should be provided on U-interface. Perhaps the author will include this in the Second edition.

If you need to know about the ISDN, network syncronisation and non-advanced SS7 this book is the best. It is a shame though that the book does not cover SS7 user parts such as SCCP,TCAP and due to date of publication does not have BISUP, Etc. The book is extremely well written.

This book is packed with ready to use information on SS7. Eversince I got hold of this book, I have used it on numerous occasions in my work. Though I bought it mainly for SS7, I found the chapters on network synchronization and timing truly revealing. Very few telecom engineers are aware of the significance of timing in telecom networks. I do not know of any text that treats this subject so convincingly. In conclusion, a great work.

David Fogel has done a painstaking job of examining the historical record of Evolutionary Computation (EC) and recording both early and seminal papers in field. As a lecturer on EC, I have found the book to be an important, intriguing and insightful supplement to the course.

I think the book's strengths are twofold. First, that the important ideas in EC "popped up" in many earlier guises. I find it fascinating to discover concepts like "schema theory" and "bloated programs" addressed in at least a primitive form in papers going back to the 1950's. EC may be a "new science" but it clearly has deep roots. Second (and a more general point), that ideas themselves are not all that is required to do science. Timing and other factors play a role in how ideas get pushed forward and recognized by other researchers. It is a point that would be well taken by young researchers in any field.

There are some things that could be improved. One could quibble about the selection of papers, though I think Dr. Fogel's selections are well justified. For readability's sake I think the formatting of some of the papers could have been redone. Furthermore some papers might have been better presented in an abridged format. Overall, however, I think the book's minor flaws are far outweighed by its contribution to the field. Serious students in EC should definitely look at this book.

The collection of papers included in this book not only serves to explore the origins of evolutionary computation, but also shows some contributions that could had been turning points in the field but that somehow never received enough attention. The comments of David Fogel preceding each chapter are refreshing and show a deep and extensive knowledge of the field. His meticulous work of selecting, editing and commenting this valuable collection of papers certainly deserves my highest admiration. I have decided to use some of the papers contained in this book for my Graduate courses and seminars on evolutionary computation because I think that these early attempts (either successful or not) to simulate evolution in a computer must be studied by any serious EC researcher.

This is not your ordinary volume of collection of papers, this is a treasure chest for all those who truly want to understand the "evolution" of the ideas behind contemporary Evolutionary computation. David Fogel's thorough knowledge of the field and his passion for>tracking down the origins of the key ideas are evident in his introductions to each group of papers. Each time I have opened the book I have made delightful and often quite unexpected discoveries for myself. I wish to thank David Fogel for this outstanding work.

Evolutionary computation techniques (i.e., techniques based on the metaphor of natural evolution) constitute one of the most fascinating areas of computer science. Despite a long history of research spanning over several decades, evolutionary techniques are still of increasing interest because of their applicability to many real-world problems in science and engineering. However, many recent discoveries have their roots in the past (this is probably true in any discipline of science), and perforce, it is important to "look back" at some of the early developments in this field. Apart from the interesting ideas that emerged many years ago (e.g., artificial life, co-evolution, evolving computer programs, etc), a number of papers in this volume contain latent ideas that have not been fully exploited.

David Fogel accomplished a great feat by searching, reading, and selecting a collection of papers that constitute "the fossil record of evolutionary computation." This volume contains almost 30 important research articles that establish the foundations of evolutionary computation, including seminal articles written by Ingo Rechenberg, Lawrence Fogel, John Holland, Hans Bremermann, Nils Barricelli, Alex Fraser, Michael Conrad, and John Koza. All the articles were grouped carefully into meaningful units, each prefaced by an introduction written by David Fogel.

Researchers will find this volume to be an extremely interesting guide to the background of concepts of evolutionary computation. It is appropriate for anyone who is in search for such answers as: where did these techniques come from? where are they going? and what is their potential? But, above all, the book provides a unique experience of addressing the most fascinating question: "how is an idea born"? For this reason alone, this book is a must for any researcher in this or any other related field.

A rare piece of scholarship by one of the leading scientists in the field. Evolutionary Computation has only recently matured to the point of being a separate discipline. The Fossil Record is a remarkable compilation of foundational research. Fogel does an excellent job of placing each work in its historical context. In many cases, he was fortunate enough to interview these pioneers of computer science, artificial intelligence, mathematical biology, engineering, cybernetics, and evolutionary theory. As such, he provides unique insights into the motivations, methodologies, and philosophies of some of the most original thinkers in science.

Russell W. Anderson, Staff Scientist, HNC Software, and Associate Editor, IEEE Transactions on Evolutionary Computation

It's rare to find an advanced computer science textbook that's both so engaging and so informative. I've only read the first seven chapters so far, but when I sat down to write my first genetic algorithm (for real research use), the book had already prepared me well.

It's hard to imagine a better introductory textbook for this topic.

This book is a great introduction to genetic programming and should be a model for textbook authors in other fields. Knowing little about genetic programming to begin with, this book guides the reader through the various topics and problems associated with genetic programming in a very logical and understandable way. Highly recommended! I wish more technical books were like this!

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.

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.

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.