Fuzzy-Logic Books

I'll be honest, I bought this book at a garage sale (read "at a discount"), and it was totally worth it. It's full of awesome examples of how to apply some pretty heavy concepts. However, the code examples frequently won't compile, and are replete with errors.

I bought this book because of the chapter O'Riley had on its site (Flocking) and the general experience I have had with O"Riley in the past. While there is plenty to learn from this text, its not for the faint of heart or new programer. There is a lot that needs to be done to get set up for this.

My first issue is that some of the code seems just a little too complex for a beginner. While I respect the features hes trying to put in, it can clutter up the main point of what is happening, and makes learning the basic principles harder.

It seem the writter assumes you read his other book 'Physics for game programer' since he refers to it several times.Download the sample code for the book and you will see what I mean.

Then there is no discussion of the graphic package being used. I tried to do the stuff with GDI+ and ended up switching to DirectX because the flickering was so bad. Some discussion on setting up a test and development enviroment to run these projects on would have been helpful.

Oh and it was written in C+. Okay, no big deal, but a warning would have been nice. I can handle C+, but I do my work now in C#. Since it was written in an OO language, a little back ground on system design would have been helpful too.

Asking too much? While the info there is good, there are a lot of obstacles for a 'beginner' to handle. I'm motivated though, and bought his phyiscs book just to see if it helps out any.

This book gives people that are new to AI in game programming a quick start in that area. If you are interested in looking at the broad fields of AI with direct application to game programming, this will show you a bit of everything. The text is clear and doesn't require any higher understanding of mathematics than some basic trigonometry. I think that the problem most people have with this book is that none of the chapters covers its subject in depth. Thus, people looking to learn AI from this book that ignor the "Game" part of the title will be disappointed. Full C++ sample programs are available on the books web site-the book is all in C++, and you should have no problems understanding the code with moderate C skills. Bresenham's line algorithm, line-of-sight-chasing and intercepting are all explained in a pretty simple way. My biggest complaint is that, even within the construct of game programming, the presentation of Bayesian systems and probability was too short for my taste. The following is a description of the book from the context of the table of contents:

Chapter 1, Introduction to Game AI - Defines game AI and discusses the current state of the art as well as the future of this technology.

Chapter 2, Chasing and Evading - Covers basic techniques for chasing and evading as well as more advanced techniques for intercepting. It also cover techniques applicable to both tile-based and continuous game environments.

Chapter 3, Pattern Movement - Pattern movement techniques are common to many video games and developers have been using them since the early days of gaming. You can use these techniques to preprogram certain behaviors such as the patrolling of a guard or the swooping in of a spacecraft.

Chapter 4, Flocking - The flocking method examined in this chapter is an example of an A-life algorithm. In addition to creating genuine looking flocking behavior, A-life algorithms form the basis of more advanced group movement.

Chapter 5, Potential Function Based Movement - Potential-based movement is relatively new in game AI applications. It can handle chasing, evading, swarming, and collision avoidance simultaneously.

Chapter 6, Basic Pathfinding and Waypoints - Game developers use many techniques to find paths in and around game environments. This chapter covers several of these methods, including waypoints.

Chapter 7, A* Pathfinding - No treatment of pathfinding is complete without addressing the workhorse algorithm of pathfinding; therefore, this whole chapter is devoted to the A* algorithm.

Chapter 8, Scripted AI and Scripting Engines - Programmers today often write scripting engines and hand off the tools to level designers who are responsible for creating the content and defining the AI. In this chapter, you'll explore some of the techniques developers use to apply a scripting system in their games.

Chapter 9, Finite State Machines - Finite state machines are the nuts and bolts of game AI. This chapter discusses the fundamentals of finite state machines and how to implement them.

Chapter 10, Fuzzy Logic - Developers use fuzzy logic in conjunction with or as a replacement for finite state machines. In this chapter, you'll learn the advantages fuzzy techniques offer over traditional logic techniques.

Chapter 11, Rule-Based AI - Technically, fuzzy logic and finite state machines fall under the general heading of rules-based methods. This chapter covers these methods as well as other variants.

Chapter 12, Basic Probability - Game developers commonly use basic probability to make their games less predictable. Such cheap unpredictability enables developers to maintain substantial control over their games. Here, basic probability is covered for this purpose as well as lay the groundwork for more advanced methods.

Chapter 13, Decisions Under Uncertainty--Bayesian Techniques - Bayesian techniques are probabilistic techniques, and in this chapter you learn how you can use them for decision making and for adaptation in games.

Chapter 14, Neural Networks - Game developers use neural networks for learning and adaptation in games for anything from making decisions to predicting the behavior of players.The most widely used neural network architecture is covered here.

Chapter 15, Genetic Algorithms - Genetic algorithms offer opportunities for evolving game AI. Although developers don't often use genetic algorithms in games, their potential for specific applications is promising, particularly if they are combined with other methods.

Appendix, Vector Operations - How to implement a C++ class that captures all of the vector operations that you'll need when writing 2D or 3D simulations.

All the chapters in this book are fairly independent of each other. Therefore, you generally can read the chapters in any order you want, without worrying about missing material in earlier chapters. The only exception to this rule is Chapter 12, on basic probability. If you don't have a background in probability, you should read this chapter before reading Chapter 13, on Bayesian methods. I would recommend this book if you are looking to implement AI into a game without wanting a complete explanation of the theory. If a complete explanation of the concepts is what you require, you will be disappointed.

AI for Game Developers is a book aimed at beginner game programmers that want to apply AI techniques in their games. The range of topics covered is vast, chasing, flocking, pathfinding, state machines, bayesian networks, neutal networks, genetic algorithms, fuzzy logic and more.

The authors spend time to explain these AI concepts from the ground up, with numerous code samples and accompanied by full programs including GUIs & simulations, downloadable form the book's website.

So far all good, but not really so if you look a little closer. For a programmer with more experience than the complete novice, many problems become apparent quickly:

The code listings ("examples", as the authors uncommonly call them) are lacking in many aspects. The code is of low quality. C++-- some call it, and it's an appropriate name for the code of this book (take a big program with a bunch of globals and void foo(void) operating on them, wrap it all (public) in a class, and call it Object Oriented). The principal author is a scientific programmer, which shows well since the code looks sometimes like a port from Fortran. The code is also poorly typeset, in a font almost identical to the text, which makes samples hard to spot and follow. The authors also paste huge amounts of code in the book that sometimes fill whole pages, without any apparent reason. Another little deficiency is the typesetting / overall formatting quality of the book - some diagrams are simply missing, fonts are uncomfortable (especially the mix of code & text)...

It seems that most of this book's problems are about the code, though. On the conceptual level, the book is not bad. As far as I can judge, the explanations are clear and even novices should have no trouble understanding how the algorithms work. Just look away from the code, please !!

Terrible and useless even for a book on AI for budding game developers. The theory and explanations in this book are sometimes decent but more often than not quite lacking. (es: in one of the first chapter the author uses Bresenham algorithm without taking the time to explain it). The use of tile based examples introduce unnecessary overhead, and the continuos attempts to introduce physics related code and references to the author's other book on game physics are just plain annoying. The range of subjects covered is very broad (chasing and evading, pathfinding, emergent behaviours, rule based reasoning, bayesian networks, neural networks, fuzzy logic, finite state machines, genetic algorithms), definitely too broad to treat each of these subject in decent depth and with clarity. Example code is of low quality and just superficially object-oriented. If you are looking for a decent introduction to game AI I recommend Matt Buckland "Programming Game AI by Example" and "AI Techniques for Game Programming".

I recently used the book in an introductory AI class. I found it short on good descriptions of the basics, and long on 'user manual' information on FuzzyTech. This was not bad in itself, but FuzzyTech is a VERY complex program and the 'trial version' on the CD will not let you save ANY files or projects. This means you have to do all your learning in one session, or start over the next day. It would have been far more useful if the company had limited the size of the project you could save. I won't use this book again.

I found this book to be a worthwhile read. I agree with the other reviewers that it covers Fuzzytech quite extensively, but a completely working version of fuzzytech ships with the book, so it is possible to follow all the examples in the book. The book triggered some good ideas for me as to how to implement fuzzy logic in the business environment. It does not try to be a very academical book, although various discussions are given to explain Fuzzy Logic. If you are prepared to use Fuzzytech as tool to play around with examples, then this is a good book.

As a user of the fuzzy logic program that von Altrock's company makes, I have found that this book is absolutely necessary. The truly weird thing is that Inform, the software publisher, doesn't tell you about this book, when it should be included with every Fuzzy program that they sell. The manual that is included with the program is wretchedly bad; dull, confusing, and pointless. Only worse. Once you discover this book, much of the operational confusion surrounding Fuzzytech will be cleared up. However, von Altrock cannot resist a certain measure of obscurity. NeuroFuzzy applications is direct and clear, but leaves plenty of understanding gaps between one implementation and another. Von Altrock needs to expand this text and provide a wider range of specifics and details. For instance, until very recently, Fuzzytech suffered from a limited ability to read data files. This placed the program far behind the curve of contemporary usage. This is badly needed information; how does the progam really work ? Since this is the ONLY readable volume on the subject, von Altrock and Inform would be well advised to do a more thorough job of linking theory to practice.

This book has a promising blurb which lead to me buy it. I was greatly disappointed. The blurbs suggested that the book would have plenty of detailed examples for the use of fuzzy logic in business and finance. The examples were there, but few and far in between, without the detail that would have made them useful case studies. Instead the author spends almost the entire book on one *single* fuzzy logic software called fuzzytech. The book is more like a manual for fuzzytech applications than it is an exposition on the use of fuzzy logic for business and finance.

I was looking for a good technology to implement risk assessment systems and a colleague pointed me to fuzzy logic. Browsing the various books, I was flooded with mathematical theory and application notes that just claimed, fuzzy is good because it is fuzzy, and gave no hints of what was really done. Altrock's book is different. It goes right to the point and shows you all the works with examples. While the first examples are rather simplistic and only serve a didactic use, the more complicated case studies are quite useful. What is really helpful is the attached software. However, the attached CD is a bit outdated. but I was able to download an updated version of the software examples.

Overall, this is a good book on the various subjects it covers, but I have to wonder - why would you buy this expensive hardcover version when the paperback version costs a little more than half what this hardcover costs? The contents are the same, the publication date is the same, and having had my softcover copy for two years and made heavy use of it, it seems to be standing up to the wear and tear just fine.

This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools.

The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs.

Overall, I would highly recommend this as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

This book is an overview of all of the components of nonlinear dynamics. Nonlinear dynamics is a field of study that enables well-constructed predictive modeling of systems that might be difficult to solve otherwise. Such continuous systems were first widely modeled by ordinary and differential equations, but with the passage of time there are now tools and mathematical models at our disposal that make for a much more concise model of many systems. This workbook tries to touch on all of those mathematical tools. The first six chapters of the book has to do with modeling such complex systems in general, and the rest of the book is a survey of the tools needed to perform complex modeling. The book's format is that of briefly explaining a concept in a few pages, and then presenting a computer program that demonstrates the concept just explained. The explanations are very clear and concise, there are plenty of equations shown, and the accompanying code is well commented. If you want to really drill deeply into any of the concepts then you are going to need some other books. I suggest that for further reading for the mathematically inclined that you pick up "Chaos: An Introduction to Dynamical Systems" by Kathleen Alligood. For scientists that want to see specific problems that can be solved by dynamical systems I suggest the excellent "Nonlinear Dynamics and Chaos: With Applications in Physics, Biology, Chemistry, and Engineering" by Strogatz. The only real complaint I have against this book is that there is uneven coverage of different tools. For example, the author has a great deal to say about neural networks and fuzzy logic, but has very short chapters covering discrete wavelets and cellular automata. More material would have been great, since it is hard to find good books on discrete wavelets and cellular automata in particular. Some readers may also be annoyed that much of the book are code listings of the various demonstration programs. Overall, I would highly recommend it as one of several books that anyone interested in dynamical systems should definitely own. In particular, those individuals interested in the techniques of algorithmic composition of music might find this book a good jumping off point for studying the tools and techniques that make such compositions possible.

The information was useful & approprate to the topic. I'd rank it as an average quality refence but a very poor text book.

The text is poorly written. The code is simple and easy to understand, but not very object oriented. There is not enough explanation of the code. The code is not electronically available.

The treatment was very mathematical but lacking in explanation & application examples. There were plenty of deffinitions, but not enough examples.

The topics covered in this book are all important from the standpoint of applications in physics, engineering, computer science, financial engineering, and computational biology. It is written for the person just getting started in these topics, and the author does a fairly good job of discussing them. Readers should not expect, and they will not get, in-depth discussions on these topics, as this would swell the book to 10 times the size. They will however get preparation for moving on to more advanced and complete treatments.

Nonlinear and chaotic maps are considered in chapter 1, with elementary definitions given and six different examples of maps discussed. In discussing the calculation of numerical trajectories of maps, the author deals with the problem of large initial values for the maps and how to implement these in SymbolicC++ and Java. He also shows how to write/read data to a file using C, C++, and JAVA. The exception handling capability of JAVA comes out nicely, but no performance comparison between the three languages for simulating the maps is given by the author. The language REDUCE is used to discuss the stability of the fixed points of the logistic equation, but the code would be useless to the reader who did not have REDUCE since some of the function calls are hidden from the reader. Useful programs are given for calculating the Lyapunov and autocorrelation functions. In addition, C++ programs are given for evaluating the correlation integral for the Henon map. The programs he develops in this chapter can serve as a quick benchmark for one's own programs that calculate the same quantities.

In chapter 2, the author discusses methods for studying time series, including the Lyapunov and Hurst exponents. These two quantities are of enormous importance in the study of dynamical systems, financial data, and network performance. The C++ program that the author gives for calculating the Hurst exponent will not work for arbitrary time intervals. This is followed in the next chapter by a consideration of autonomous systems of ordinary differential equations. The classification of fixed points is considered, and the important concept of a homoclinic orbit. The author gives a nice JAVA program that finds the homoclinic orbit of an anharmonic differential equation using the Lie series technique. The phase portrait of the Van der Pol oscillator is calculated using the Runge-Kutta technique in a C++ program, along with the Lotka-Volterra system from mathematical biology.

Hamiltonian mechanics is discussed in chapter 4, with the important Henon-Heiles model from astrophysics is discussed and JAVA programs given for studying its behavior using the Poincare section technique. Newcomers to this technique will appreciate seeing it done here explicitly. Integrability of Hamiltonian systems using the Lax representation and Floquet theory are also treated, but only at a very rudimentary level. Dissipation is included in the next chapter, and the author discusses the classification of fixed points according to their stability. Lyapunov exponents are again brought into the picture, and the phenomenon of hyperchaos is discussed. Some bifurcation theory is introduced with an example of the Hopf bifurcation. Chapter 6 studies nonlinear driven systems, with the Duffing oscillator treated, and the author gives a useful program for calculating the autocorrelation function of this system. The controlling of chaos with feedback and non-feedback controls is the subject of the next chapter, mostly in the context of difference maps. Fractals finally get introduced in chapter 8, with iterated function systems defined but proofs of their properties omitted. The author gives programs for calculating various popular fractals, such as the dragon, Sierpinski gasket, Koch curve, the Mandelbrot set, and the Julia set. The main disappointment in this chapter is that the author does not give programs for calculating the Hausdorff dimension or capacity, quantities that are notoriously difficult to get a meaningful computational handle on.

The author switches gears in the next chapter and discusses cellular automata, which have recently made a comeback, especially in research on quantum computation. The discussion is too brief however, and does not allow the reader to gain an appreciation of the properties of these important objects. Chapter 10 gives a brief overview of some techniques for solving differential equations, such as the Euler method and the Lie series technique. The latter is not commonly treated in beginning books so its inclusion here is helpful. Symplectic integration is also discussed briefly, but the author does not discuss how to check the integrators using backward integration, which is commonly used in conservative systems modeled by symplectic maps.

Chapter 11, covering neural networks, is the most well-written in the book, and the newcomer to the field will get a fairly decent introduction to the subject. The supplied programs serve to illustrate some of the important concepts in neural networks, such as the Hopfield model, the Kohonen network, the perceptron learning algorithm, and the back-propagation algorithm.

Chapter 12 is an introduction to genetic algorithms, and I find this one particularly nice also, as it does give a rudimentary introduction to what evolutionary algorithms are all about, and gives some elementary genetic programs that find the maximum of one- and two-dimensional maps. He also discusses simulated annealing, and gives a useful program that allows the reader to see clearly how this technique works.

The last chapter covers fuzzy sets and fuzzy logic, which has also taken on importance in recent years, especially in data mining and financial engineering. The programs given to illustrate the concepts are particularly interesting from the standpoint of coding in C++, as the author uses friend functions and operating overloading in some of them. The reader gets a good overview of fuzzy reasoning and fuzzy rule-based systems.

Here is a text of advanced nonlinear dynamics. Geared towards the intensive use of computers to perform the necessary grungework. Steeb hits on many important ideas that have emerged in recent decades. He shows the interrelation between chaotic phenomena and fractals, and how fractals can be used to describe the onset to chaos.

The Hidden Markov Models have proved to be the key idea in current Automatic Speech Recognisers. A tribute to the practical nature of this idea.

Steeb's discussion of neural networks and genetic algorithms is enough to get you started in this field. Ideas like forward and back propagation for feedback are clearly explained.

The sample code should be welcomed. It lets you see for yourself on your own computer, and to tinker with the various parameters. Though I am unsure about the choice of code in Symbolic C++. Unlike C++ or Java, this is a rarely used language.

Fuzzy Logic is the best book of its kind that I've read. Friedman gets straight to the heart of things, and doesn't get caught up in the techno-gobbledegook that mars so many other books like this.

It's a significant acheivement and an IMPORTANT book. A must read for anyone who really wants to know what's going on with new media and new technologies.

Definitely worth reading. Cuts through the Internet hype

This book is not a textbook of fuzzy logic which is a logic based on Zadeh's fuzzy sets. You should not look forward to readily learning fuzzy logics by reading this book. (Unfortunately, it means me.) For the contents of this book, please read the other reviews deeply. However, the subtile of this book and the fact that customers who bought this book also bought "Fuzzy Sets and Fuzzy Logic: Theory and Applications" on Amazon.com, are very misleading to customers.

This book is one of the best I have seen that completely covers clustering, and so many important applications of it to a wide variety of fields. The book is authored by some of the best researchers in the fields of fuzzy systems, pattern recognition and computational intelligence, so the text is complete, concise, and heavily informative.

Fuzzy Image processing in MTV'

This is the first comprehensive review of clustering algorithms with enough detail to implement and apply them that I have found. It is readable for an upper level undergrad, and is a superb reference on the mixing of fuzzy methods, clustering, and visual pattern recognition. The notation and pseudocode are very clear, and the authors tell you the practicalities of the advantages and problems with the various methods. I have written code for artificial intelligence, clustering, image processing and fuzzy. This puts it all together and would have saved me months. Bezdek is a guru on this stuff and has an incredibly clear view of his subjects.

I have used his recommended system of "Mutual Fund Investing" for the past two years. This system imposes constraints for portfolio asset allocation based on the investor's risk tolerance before buy/hold or sell decisions are made using his Fuzzy Logic concept. This disciplined method has been extremely valuable to me in these turbulent times when so many conflicting opinions on stock and bond market directions prevailed.

Maybe this is a book for someone new to mutual funds or to retirement planning - there is a lot of background for those. But if you've had any exposure to technical analysis or expect to see fuzzy logic used, this book is a disapointment. Its not really fuzzy logic - he sets absolute limit thresholds and, depending on their on/off combinations, does a buy/hold/sell. A real fuzzy logic system would have produced a proportional response to varying data. I was expecting a system that might, for example, adjust proportions between the funds available within a company 401k (ideal for a real fuzzy logic approach)- not a conventional all-in/all-out, buy/hold/sell approach like his. His system could have been presented in a small magazine article, not bloated to book size.

Peray's technique for investing in mutual funds is easy to understand. I'm a conservative investor and do not need 30 and 50% returns. I also dont want to expose my capital to undue risks. Peray's Fuzzy Logic concept has produced an all-out sell signal for USA equity funds in the first week of June 1999 (DOW JONES Industrials over 11000) and I adjusted my portfolio accordingly. I'm waiting for the Fuzzy Logic signal to get back into the market .

One of the most interesting thing about deviant logic is its widespread dismissal by the academic community despite the widespread application of fuzzy logic to home appliances and engineering devices and other aspects. Susan Haack has addressed the lacunae admirably in this wonderful book and she deserves every kudos for it. It is pitched at a not-too-technical level and should appeal to all layman and also the academics.

Wow, what a disappointment this book is! First, it is quite pricey considering it is simply a collection of Haack's papers that have been published in various journals; one would expect better editing and perhaps even a glossary but this simply copies the papers verbatim.

For those who are beginners in formal logic or who have been out of the field for a while you will likely have problems beginning in the first chapter. Who remembers the definition of "wff"?

No, Haack should have completely rewritten the papers to make the ideas and arguments approachable for all readers of this book or at least she should have included something like "intended for the graduate level philosophy student" to make her intention clear. The book needs expansion of ideas beginning with some basics as well as some "niceties" such as a glossary of acronyms and some good editing.

That said, the basic premise of the book is rather a sad statement on the present level of thinking inside formal logic. Haack quite plainly states "I do not beleve truth comes in degrees"...Indeed. From a scientific/mathematical/engineering background, I find that quite a loaded statement and indicative of a completely closed pre-postmodernist mind.

Considering the work done in mathematics, computing and science since Godel by people like Turing, Chaitin and Prigogine showing the inconsistencies that may be found at the core of formal Aristotelian-based logic and its derivatives perhaps Haack should leave her foxhole. Yes, there is no reason to keep defending formal logic's shortcomings has long since disappeared along with Newton's view of the universe.

In the end, I would highly recommend anyone thinking about purchasing this book to consider the validity of "truth does not come in degrees" and then go and buy "Fuzzy Set Theory" and Perlovsky's latest.

This is a very nice reference book for fingerprint and face recognition. It consists of six chapters each in these two topics. The first chapters are reserved for introduction to the problems, discussion of the important issues and an extensive survey of the literature. In the following chapters, latest techniques are presented for solving problems such as enhancement, segmentation, feature extraction, representation and classification. An invaluable resource for starters to get a quick view of the lietrature and learn about the latest developments.

This book has 6 chapters on fingerprinting and 7 on face identification. The 3 overview chapters are informative and somewhat useful. There are lots of references in the book. Many of the other chapters are long descriptions of new, unproven ideas with much detail and little evaluation or motivation

By chapter 3 I realized Dr. Cox completely fails to document the assumptions and reasoning behind the formulas he illustrates. He fails to even clearly list formulas in the book. He provides mini C-code programs that will quickly become dated and the book totally useless that you can spend time picking through to eventually derive formulas, assuming they are even correct at this point in time. Do yourself a favor, check it out from the library and take a look at it first. Don't get stuck like I did with an overpriced paperweight. A "first course in fuzzy logic" by Hung Nguyen may be better. I looked through random pages and at least it has the formulas, how and why they are developed. I'm going to check it out of the library first. Ours did not carry Dr. Cox's book so I could not look at it before buying.

This is the best hands on fuzzy logic book that I have used thus far. I succesfully used the first edition of the book as reference to develop real world fuzzy applications. I see that some reviewers are somewhat upset about the source code shipping with the book. It is a pity that the C++ code, is so difficult to get going with, because this detracts from some very valuable chapters in the book itself. However, Mr Cox was very helpful in providing me with updated code. I highly recommend the book.

I'm pretty comfortable with C++, so I found fixing the couple of bugs in the shipped code to be not a problem. (Quit your whining its nearly free code.) I can't vouch for the Hisss VB interface, but then I'd drive a cab before I coded with VB. There is one serious bug but its from a typo. Email me and I'll send you the patch.

On to the good part. This is the first good Fuzzy Logic book I found. I've read several others before I got to this one and each one left me more confused than the rest. Earl finnally explained what its all about and what sort of problems this technique solves. There is a bit of "Fuzzy Logic is better than Neural Nets" but no real concrete examples to prove it. I ignored that and used his examples to learn how to do this and his code in some game AI. It worked well.

Also in case you don't know the thing that Fuzzy logic does well is smooth out transistions, ie it keeps things from oscillating between two single states. It's also good for when you have multiple inputs all of which contribute to deciding whether a threshold has been reached. You set weights to the inputs contribution and analyize the result, meets the threshold or not. You can also adjust the threshold depending on the state of the object. Coupled with a Finite State machine and you've got a basic game AI.

I have also taken some time (about a week) and cleaned the code up. It wasn't too difficult and I now have an OOP interface to it which made things a lot easier to understand. Earl obviously has a for sale system using the original code. He must have cut a chunk out and put it on the disk. I also have about a dozen emails from him, and I've sent him the updates. He's a busy guy, bug him to put the fixed code on his site. Maybe he'll get around to it.

If you want a book that gives basic explanation of fuzzy logic - this one is not that bad. If you want this book because it comes with 'free' code - look elsewhere. I'm a programmer with 10 years of C++ experience but I have not seen worse code than is supplied with this book. And believe me, I've seen a lot of bad code - I even wrote some of it :).

I am about halfway through the book and in general it's a decent guide to fuzzy logic. Earl explains the concepts well and provides decent real work examples. The code, as everyone else here has already said, is basically worthless. The book would be far more valuable if he just removed the code entirely from it and focused more on fuzzy logic. Another complaint: reading the first 50 pages made me feel as if I were reading a religious text, not a fuzzy systems book. Earl spends a great deal of time convincing the reader that Fuzzy Logic easily beats out other competing expert systems such as Bayes logic and neural networks. He dismisses those who do not agree with him as "uneducated" and spends time hurling personal insults at them rather than focusing on the benefits of fuzzy logic. I almost put the book down and returned it when reading the first 2 chapters. Altogether this is a decent introduction to fuzzy logic if you disregard the useless code and pedantics of the author.

"A First Look at Fuzzy Logic and Neural Networks..." might be a lot more accurate. It does a good job of covering the concepts. What it doesn't do is address any of the issues of implementing a fuzzy system in an embedded environment. If you don't know what a fuzzy set is then you should consider this book. If you want some tips or ideas for creating an inference engine for an 8 or 16 bit processor I suggest you look elsewhere.

The book is written in a language that makes it accessible to beginners in the field of fuzzy logic as well as experts, since it contains top notch research on the state of the art of the topic.
Embedded system design using fuzzy logic algorithms is made easy through practical examples.
I thoroughly enjoyed the book. If you want a concise, well written book that is not overbearing and is actually very user friendly and you are interested in fuzzy logic application algorithms this is your book.

While this book does provide a reasonable overview, I found it rather disappointing.

It has too many errors. With highly technical material, it is imperative that the information is correct or else you can't trust it. For example a minus instead of a plus does not help when explaining terminology.

Only half the book is really about fuzzy logic. There is far too much padding eg. 1.large diagrams showing Moore's Law and the layers in an IC gate. These are not subjects that should be covered in a book on fuzzy logic and one is forced to conclude that the author had a page quota to be reached and did it by adding these secions and large verbose reference sections.

A worked example or an appendix showing an algorithm in C would have been far more useful.

For someone looking for fuzzy modeling and control into embedded systems this book is excellent. The author provides a firm fuzzy concepts necessary to design intelligent systems and gives the reader a solid background for further studies and real world applications. Embedded systems design case studies overview is something that all embedded system developers should understand but many don't take the time. It is thorough, without being arcane or pedantic.

In summary the book contains the right material, it is presented in an easy to absorb manor and is practically oriented. I highly recommended it to embedded engineering students, or engineers and managers facing the challenges of fuzzy logic based project. I'll consider five stars for this book.

Good introduction about fuzzy logic plus a ton of web resources. I gave it 3 stars because so many wording errors in this book.