Simulation Books

Hofstadter provides effectively a series of articles published elsewhere, edited in his engaging, verbose style.
Basically the question of the book how would a computer solve the following:
"X:x as Y:?"
You can get much more complex, but basically his group spents the 80's and early 90's researching this questions and trying to figure out, "know when to break the rules" applied.

His overall appraisal of AI is that even within confined realms, it still produces inconsistent results, and there is a long way to go.

Processing power is ~1000x greater than when he wrote this book, but as he observed with Deep Blue, "Brute force methods tell us nothing about Human thought".

I realized this was a small sampling of the issues facing the whole approach. Enjoy.

When I first starting reading "Fluid Concepts" I found myself puzzled; what, exactly, was Hofstader up to? He and his team of grad studenst seemed to be spending a tremendous amount of time on something that at first struck me as very trivial- solving puzzles of the "what number comes next" variety. I didn't see the connection to cognition. I put the book down for a while.

When I returned to it, after having done some refresher reading in cognitive psychology, Hofstaders' intent was much clearer. To understand his program, you have to start by discarding GOFAI ideas about the stored representation being primary, and look at the problem as a psychologist would: Before you can even ask how representations are stored, you have to ask how they got there in the first place, and that's what Hofsatder is looking at here.

Perception consists in large part of taking a mass of sensory data, and looking for patterns- in it. That's a critical part of cognition. It's both how we extract words from marks on paper or sounds uttered by another, and why we see a face when we look at a full moon, or a stain on a curtain, or a piece of burned toast. Hofstader and his team are looking for those fundamental processes that allow to both match raw perceptual data to representation, and to generate those representations in the first place.

Since the publication of this book he's moved on to another research program, and having been away from the field for over a decade, I'm not sure how influential it has been. But as far as I can tell, no one else has done as in-depth an analysis of this sort of primitive pattern matching, and for that reason alone, I think it's a program that every cognitive scientist should familiarize themselves with to some degree.

I read this book when it first came out. At the time I had a deep interest in all things AI. The book presents Dr. Hofstadter's experiences (along with those of his graduate students) of implementing creativity modeling systems (and others) at the Fluid Analogies Research Group (FARG). The book is not an easy read. The reader will need to be diligent and not get deterred. The book also is a bit dry in areas, but those who are truly interested in the subject matter will not mind, much.

This book is, as others have commented, different from DH's other more entertaining books.

It is a serious attempt to discuss the real issues and difficulties with AI research. There is a lot of quite dry material and in places it is repetitive.

It provides terrific insight into the problem of imitating human thinking at a deep level, and I found it very rewarding. It was also very interesting to follow the threads of how he went about doing research, and what he thought of other AI research.

His views of various flavours of AI research were very instructive and inightful I thought.

In summary a good book, but this is not (high quality) brain candy like Godel Escher Bach etc.

Many books by D. Hofstadter are at the top standings of my personal parade, but in reading this book I found myself very likely too distant from my usual interests and preferred styles. The initial part is very interesting, but when the author carries on detailed descriptions about programs' features in conversational shape, I have been quickly bored, and I have given up attentive reading turning to an eagle eye approach. I would have been by far more comfortable with a more formal explanation, because, once I make the effort to follow the thourough description of what and how a program does, it is more convenient to study its algorithms.
So, the book is surely very pleasing for people professionally involved in semantics, but I am not confident in its general interest.

I was very happy with my purchase. The book was in perfect condition, shipped quickly, and cost much less than my university's bookstore.

It is full of errors. The explanations are difficult to follow. There are few highlights in the text which makes scanning for a quick review impossible. There is no chapter summary. The book presumes a thourough knowledge of Excel which many students do not have. Stay away!

By incorporating Microsoft Excel spreadsheet examples of the problems, the authors have managed to make self-study management science possible. I'm absolutely convinced this is the best way to learn MS.
Anyone that has responsibility for making business decisions should keep a copy of this text nearby.

Previous reviews inspired me for the purchase. This book is NOT MBA material. I would rate it at Business 101 book. Most spreadsheet models are basically the same using the SOLVER function in excel. There are better tutorials online.

Used this book in B-school and loved modeling using @Risk (@Risk is the modelling software that comes with the book - pretty much self intuitive). My only complain with this book is that it was very focused on getting to the answer fast than really exaplaining the process and modeling techniques. After doing few examples you start to develop the intuition ... but I feel that the author could have done a better work in explaing the process behing modeling.

It is a very good book for a Data base designer and a data modeler. I strongly recommand this book to all database people.

This book oversimplifies the examples and expects a leap of faith to truly understand the information engineering technique of data modeling.

May be good in the class room; but in actual practice there are much better references available such as Silverston, Inmon, Kimball, and of course the Zachman framework.

Anyone that has been modeling very long will see this book for what it is ... after you look at it once, you'll put it on your bookshelf and leave it there. Save yourself the money ... There are much better reference books available. Try David Hay's book on patterns, or Len Silverston, or Graeme Simsion. Check out the DAMA reference guide .. at least it's built by actual practitioners.

The help screens on the Data modeling tools are more advanced in explaining data modeling than this book.

Probably great for theorists - managers or teachers that don't know what they are doing! But the real modelers will seek help elsewhere.

This book is about as much fun to read as a book about differential equations. Good concepts, but the context is very dry and puts me to sleep. I've been in the industry for several years, and I bought this book as a reference. But I find myself cringing every time I need to use it.

The authors deny the fifth normal form and state special-case rules as if they were universal. Examples: Eliminate triads; Two entities cannot have more than one relationship. Although in some specific situations the advice might be valid, anyone who is trying to learn from the reading will be misled. Less harmful, even interesting, for a professor (to learn how not to approach the teaching of DB modeling).

Poor, underdocumented examples. Oversimplification. Unfortunately at the time I had only the title to choose from. Good thing most books now have a table of contents.

Database modeling still doesn't have strong references as database theory does (Date's, Ramakrishnan's, Elmasri's only to cite three). There are excellent theoretical (Thalheim's "Entity-Relationship Modeling" is good) and philosophical approaches (finally they re-published Kent's opera-prima "Data and Reality", fabulous).

The picture is poor when it comes to hands-on modeling. Bruce's "Designing Quality Databases..." is an exception. Good and useful for someone who is developing modeling expertise. But I especially don't recommend Reingruber&Gregory's book.

The book covers many different simple circuits and gives a few designing tips but it does not cover math nor enough details about the circuits, however a book that can be finished in a few weeks.Recommended for first or second year students.

What is the software version

First of all let me state that the Electronics Workbench program looks very interesting; what I've seen of it. The little demo that's on the CD-ROM only allows for extremely small circuits. It's barely a demo. It's a tease, but you can see the program's potential.

The author has presented some electronic material that's been around and published in many books. It's presented in a matter of fact manner. If he still teaches students, I'd try to find another class; one with more enthusiasm in the air.

I formally got into electronics in 1961. I built my first Allied Radio receiver around 1959. I loved to listen to the radio amateurs talk about their "Home Brew" equipment they were building. My point is that electronics should be fun, exciting and an adventure. It should not be a chore. It should not be boring.

There's nothing wrong with the simple circuits in the book. It's almost as if the Electronics Workbench demo was added to sell a book full of stale material. Then the title was juiced up to allow a potential buyer to think the book was about the use of Electronics Workbench with these hand-picked circuits. Not so. Except for six short statements before chapter one ( a clue ) the author barely alludes to the Electronic Workbench program; leaving the reader to figure it out on his own.

In conclusion I'll just say that this whole purchase and experience could have been much better if the Electronics Workbench demo would allow for more components in a circuit and if the author could have alluded to that program in his text.

A comprehensive beginners guide, but not only that but a book able to help some of the more experienced. It teaches you how to simulate both a circuit as a whole or a circuit broken up into modules to test their practical capability. It does not bother to paraphrase what is already in the manual but takes the reader into the realms of circuit design. Consequently I have found this book worth its weight in gold, as it has saved me many hard hours work and I have had the great pleasure of being able to toy with new ideas effortlessly.

This book is NOT about using the simulator program Electronics Workbench. It is a rehash of some old magazine articles about electronics, written at the hobbyist level or lower. It has NO useful information about the software. If you already know ohms law and want to learn Electronics Workbench forget this book.

This is the best training book by far for Maya character animators. Even though the program is now dated, the theories and exercises are excellent and Phil Young's illustrations are very clear and concise. Young is a traditionally trained artist/animator so he knows what he is talking about, and he translates 2D physics to Maya very well.
The book is concise and well written and the illustrations are plentiful and simple to understand. The best feature of this book is that the enclosed CD contains the generic animation figure "Generii" created by Andrew Silke. Generii is used for the exercises instead of the usual 'realistic' (and often extremely poorly designed)character. The well-planned exercises and explanations work for any CGI program, so it is too bad that the title is going to date the book badly--look past the title and get this book if you are interested in learning character animation in CGI.

This is the one book out there with animation in the title that actually does animation.

I appreciate the study of movement presented in this book. It isn't rehashed from other books - it is fresh and makes a lot of sense. The wave theory is great - and is easy to do in 3d.

This book talks about the graph editor in huge detail. I got a lot out of it - especially since no other book does this.

This book is terrific for learning to animate. I was happy with the traditional technique that was explained alongside the Maya. I did not run into the problems the other reviewers wrote - my book was fine and the tutorials were easy.

It was cool to work with this book because it focused just on animation. I bought a $50 book called animation, and it was all about modeling and rigging. I appreciate that this book was written by Disney guys, and kept me focused on movement.

Almost all the chapter files on the cd would open with errors, so they were practically useless. And for Ch.7 it says there are reference pictures on the cd for the throwing exercise, but there are no pictures. Also, there's a bunch of little typo's, but that's forgivable. This book is really easy and fast to read, I consider myself a beginner, but I guess I was a little more advanced than what this book had to offer. Overall, this is a decent book, but it isn't as great as everyone has been saying....

This book is good if you already know how things work in Maya.

If you are a beginner you will feel like someone dumped an 18-wheeler truck on you. The descriptions of tools and how things work are barely explained and then you are given exercises to do using those tools. The exercises say to start with a shape as shown in the picture and then "tweak" the shape until it looks like the other picture shown. I don't see how that can be called instructional. Unfortunately, how to get from one to the other is a complete mystery. I unsuccessfully spent several hours just trying to get anything accomplished with this book. I don't feel like I learned anything. The book seems to be written for those who know Maya's basics and want to get on with building. If you are new to Maya, AVOID this book. I am good at learning new programs generally speaking, but this book makes it hard and not fun.

This book gives a very deep insight in the problems of the creation of systems with some intelligence.

I seldom pan books, but this one is little more than an egotistic rehash of simplified versions of AI/AL theories of the past 3 decades. The only new data are the author's opinions. If you are looking for anything new and/or in depth, look elsewhere.

There are some interesting analogies and examples of perceived or emergent behaviour but overall many of the arguments do not hold up to scrutiny. If you are looking for a book written in the form of opinions, as opposed to hard facts, then this book will be more to your liking. Certainly something I would borrow from a friend/library rather than paying for it to sit on my shelf - not something I will go back to in future to read again or for reference. It was a disappointment as I was led to it from Richard Dawkins' excellent "The God Delusion".

I must say I enjoyed the book completely. While I don't agree with the author on all points - the book is incredibly thought provoking. I was so glad to see such a book written that after I read the book (in 3 nights - short book) I bought three copies for co-workers who I wanted to read it. Steve Grand is now quite famous (or should I say even more famous) after writing this book. He has challenged traditional thought on the subject of AI and in a way that has made converts out of many.

However, he spends 10 chapters saying "you are all wrong - this is the way to do it" - then doesn't follow up on doing it himself but rather takes enough shortcuts to make the work suspect - but to his credit he does say he's doing going just that :) All in all - if you're a software engineer or software developer I highly recommended the book.

Grand's book isn't that at all, although it tries to be. He starts out with his definition of life, and builds (slowly, oh so slowly you could cry) up to the point where the rubber hits the road, so to speak. At that point, he imply handwaves the entire process of programming a-life.

So in short, there are books out there that do a better job of explaining the application of neural networks. There are better books on the philosophy of consciousness and life. There are better books on game design.

So you don't need this one, because Grand only tells you what you already know, if you're at all interested in the subject, and doesn't add enough best-practice techniques to make his way of building a-life better than any other. It's as though he was so worried about giving away his secrets that he redacted all of the information in the book that would have made it more than 'Here's my philosophy.'

The only thing saving the book from a one-star review is that the first 10 chapters do light a fire in your belly to find out more. But this book isn't going to provide that 'more' that you want to know.

As the "new kid on the block" in my data architecture group, I attended my first DAMA conference in March. One of the sessions I sat in on was given by an IT manager for the Department of State in Washington. The speaker ended her talk with five things they did to make their project a success, and one of them was giving Data Modeling Made Simple to everyone in their department, even the business folks.

I made a note of this title and did not buy the book until recently, but I'm glad I did and wish I bought it sooner. I was able to read the book cover to cover during my lunch break in less than a week and picked up some great messages. Here are the techniques that make this book five stars:

1. The business card example - explaining data modeling with something so simple like a business card is a great method, and I should have bought this book back in March just for this example. A business card is chock full of data and is used to tie all of the data modeling concepts in the book together.

2. Normalization - this is a topic I used to struggle with before reading this book. Steve's simple steps in Chapter 8 are easy to follow and remember.

3. Data Model Scorecard - this is how Steve reviews a model. A template is provided that my company is using and so far the feedback is positive.

The one thing I think Steve should have included in the book is a comparison to other modeling notations. Steve uses information engineering (IE) notation and I would like to see a short side-by-side comparison with IDEFIX (which we use here).

Data Modeling Made Simple is easy to read and understand, and I think it is true that someone that does not have a technical background can also benefit from reading this book.

Mislead by other reviews. Covers only basics of ERD style modeling. Not current with any UML approaches. If you only do Oracle and have never modeled, this might be a good start. Would have returned it if I could.

The word "pain" comes to mind when reading this book. I was
looking forward to find out what a "master" data modeler might have
to say and the knowledge imparted. I was disappointed within the first
couple of pages. The second huge word that comes to mind right
from the start is "confusion". Unless you are a database guru
you will find the explanations in the book utterly confusing.
To give an example: the concepts for candidate key, primary
key, alternate key, surrogate key and foreign key are all
explained within the length of 1 page! You tell me you've
mastered those concepts by reading only 1 page (page 30)?
Are you kidding me? What is the author thinking? Is this a
dictionary or a book to learn from?
Data modeling can be quite complex especially when it borrows from
data base concepts. When data modeling is made "Simple"
(as the book's cover states) then it becomes useless.
As useless as this book is.
Seriously! I'm not trying to knock it. I'm just being straight forward.
This book does not explain anything that a person can pick up
and say: "oh I understand that", "it's clear to me". Surprisingly
disappointed. Sad book. Is there something less than 1 star?
(And I actually read the reviews by the other people who gave it
5 stars before I bought it).

The author did a good just in explaining in a simple way the sometime complexe world of data modeling.
I recommend it.

Think what you want, but to me there definitely IS a difference between books about data modeling written by nonpractitioners and practitioners. Same subject, but sometimes poles apart in terms of quality and readability. Theoretical background is certainly essential for a good data modeler, however many books written by nonpractioners overcomplicate things and fail to bring their points across in an easy to understand language. Likewise there are books by practitioners that seriously lack quality. The book at hand combines the best of both worlds and is a pearl among the entry-level books about data modeling. Easy to read and understand, concise, and straight to the point with "just enough" theory. If you are a beginner in data modeling, this book will help you in getting started quickly and in the right direction. If you are an advanced (or even expert) data modeler, this book is a good reread to refresh your knowledge.

This book is not for the faint of heart - you should know statistics and have a very solid math background before you attempt to crack open the cover. While primarily focused on risk analysis within the finance and insurance industries, the principles outlined within can be carried across to other fields such as high-tech fraud. The probability calculations, Monte Carlo simulations, and other means of determining likelihood of an event occurring are all covered and will confuse the novice. Containing a slight bias towards Vose consulting services (where the author obviously hails), this book also points out what above-average risk consultation services should do for you, as well as what you, as a hiring manager, should expect.

All in all, I find this to be a great resource, and look forward to sharing the book with others in my department that are mathematicians and can truly appreciate the content.

A very good book, but a bit too much mathematical detail in deriving formulas for probability distributions; could use better descriptions of when to use each probability distribution.

Unlike in the first edition, the author seems to have tried his best to eliminate any reference to any simulation software in the second edition. Result: it now reads like any academic simulation text, only less. The first edition wasn't broke. Why fix it? Bring back the classic Vose!

This book gives a deep insight into the state of the art and recent developments of quantitative risk analysis using simulation methods. Describes topics such as second order risk analysis I never heard about before. I used the knowledge drawn from this book to write some technical papers (published on peer-reviewed journals and seminars proceedings). Specialized software, such as @-risk and crystal ball is not strictly needed to carry out the risk-analysis systems suggested by the author (but pretty advanced skills with excel or use of math softwares are required). The specific subject of the book is risk modelling by Monte Carlo Simulation and Bayesan analysis; it does not deal with fuzzy models or other uncertainty-propagation methods. I highly reccomend this book to anyone interested into the specific subject.

I believe that this book is the best of many Risk Analysis books. The book's structure, starting from fundamental topics and guiding to advanced topics, is excellent. So, I translated this book into Japanese! You will make the best use of the book with Excel add-in Monte Carlo simulation software like @Risk and Crystal ball that you can get its trial version from the vendor's site(free!). But, the value of this book is not decreased with its sophistitated notation even if you don't have such software. You can enjoy the logic of Quantitative Risk Analysis. Now, the author is preparing his original software. I hope it will be as valuable as this book.

This is an update of a classic book on procedural texturing and modeling by the main founders of the field. The book presents lengthy discussions of classical procedural texturing using various noise functions of the sort originated by Ken Perlin (one of the authors). It discusses newer texturing techniques such as cellular texturing, which can be used, for example, to create convincing stone patterns. Other chapters focus on animating solid textures (e.g. marble forming, volumetric gasses, etc.), fractal terrain generation, and tips for utilizing existing graphics APIs and hardware for realtime procedural texturing. This is only a sampling of the topics covered.

Code samples in C and RenderMan are given throughout, although most algorithms are given in only one of those languages. This can be a bit of a problem, as many readers will probably not have access to a RenderMan implementation. Nevertheless, it is not too difficult to translate the RenderMan code into C code in many instances.

The biggest drawback to this book is its lack of rigorous technical coverage. The decision to omit many mathematical details was a conscious choice on the part of the authors. Instead the book is mostly prose discussion of the techniques and the coarse descriptions of the underlying concepts. Although the prose is mostly clear, many times I felt myself in need of more specific, technical details. Fortunately, the book's authors are the primary researchers in this field and most of the ideas in the book have been published in academic journals. It was very easy to supplement the book with these primary sources.

Overall I found this to be a very interesting and useful book, with many algorithms essentially ready-to-run right out of the book. It would get five stars, except for the lack of technical and mathematical details mentioned above. Every serious worker in graphics needs to have this book on their shelf. I use mine often.

I'm using this book because I use a shading programing (shaderlab pro 2)language for truespace that is derivitive of renderman. In that sense it was helpfull becuase it filled in the gaps of the poor docs that came with shaderlab. It took me from scratch to a basic understanding of procedural coding. Oddly, the one thing it didn't include that I assumed would be there was a discussion of the worelynoise function and feature points. This was totally strange because one of the authors was worely! Even stranger was that "advanced renderman" did do a decent discussion of it, so now I'll have to buy that! Some people might want to check out "advanced renderman" because it's less intense mathematically and gives more basic insight to renderman usage.

This book has several serious problems.

The most glaring is that a significant number of the examples are coded in the "Renderman shading language". This language serves, in this book, to hide detail, detail specifically related to producing textures. Of course, if you know the language, you're fine - but most won't know the language and so this is a grievous error.

By way of welcome contrast, other examples in this same book are instead presented as C code fragments or functions. That's just the ticket - using a broadly known, freely available, relatively low-level language with no recourse to unknown hidden graphics functionality is precisely the way to go when explaining ideas in the domain of those this book is intended to convey.

The second problem is one of content. While being concise to the level of a math text is not desirable, this book contains a very sparse field of useful information considering the number of pages. The margins are too wide, the text too large, the form factor of the book too small, and the authors too wordy to possibly convey a good basis for texturing in general - it is a broad and fascinating field, touched only in the briefest and most unsatisfying manner by this book.

I do take issue with the reviewer who complained about the exposition on how to make a brick texture; that area of the text, while it may be already quite familiar to many who are interested in texturing, contains precisely the level of detail that needs to pervade a book of this type, and detail about steps that underly critical basic texturing ideas. Without understanding those basic texturing tools, a novice misses the first step on the stairs and fall on their face. The problem is, this approach is not consistent for more complex ideas in this volume, few as those actually are.

The book is entitled "Texturing and Modeling". While there is a moderate amount of texturing information in it, whatever you do, don't get it if modeling is your goal. It is very nearly devoid of modeling information, and what there is (smoke, a planet simulation, a few other items) is very basic indeed.

Finally, as a general critique, the authors (all of them) need to learn the basic idea that when presenting a function in any language to a new audience, one should precisely define the domain (and rationale) of the inputs and outputs of the function. As an example, one might encode the function for Perlin noise, and have no idea whatsoever as to what values to feed it to get particular types of results. For those of us who can read and understand what the function is actually doing (which is esoteric, make no mistake about it) the answers will eventually be illuminated by careful study of the function. However, this is very advanced material, and I am absolutely certain that many readers will be unable to figure out how to effectively use this function without a great deal of trial and error. You can also read that as "wasting a great deal of their time." That is because they won't be learning anything that could not have been conveyed by the author(s) in a single short paragraph of domain information.

In summary:

The 2 stars is because I didn't think this was a very good book. On the other hand, it is one of the very few books that deals with the subject at all, and for that reason, you should definitely own it if textures are an interest of yours.

If you're newly interested in textures, this will give you a basis for further exploration. It won't give you a cookbook by any means.

If you're looking for cookbook and "how to" approaches, get on the web and the newsgroups.

Finally, if you're considering writing a good book about creating textures, by all means, please do. The world needs a good one: this most definitely isn't it. I'd be delighted to be one of the first owners of your new book.

This book is for experienced programmers who want to understand the fundamentals of procedural graphics generation. This book is not for artists looking for practical applications of procedural texturing and modeling concepts.

The authors cover a very large array of topics in the field, including many pertinent code examples, mostly in the RenderMan shading language. It focuses on the groundwork of the field from the first texture maps in the 70's onward, with a cursory mention of the state of the art at the time of publication.

Representative text:

"The particular kind of fractal we're building is called fractional Brownian motion, or fBm for short. fBm is characterized by its power spectrum, which charts exactly how amplitude relates to frequency. Oops! Pardon me - I'll knock off the math."

"Long ago I gave this idea the wonderfully unpretentious - not! - moniker "generalized Impressionistic texture," or GIT for short. (We need more TLAs - threeletter acronyms.) The GIT matrix generator system takes the form of a time-varying swarm of color samples in a color space, usually the RGB color cube."

This book has five authors, and that is exactly the way it is written. It changes character practically at the beginning of every chapter. It is obvious that the authors have a great deal of knowledge of procedural textures and modeling, however, it is all just lumped together into one big hard-to-sift-through mountain. You will have to do a great deal of work to extract algorithms from this book. Only because there is good information there do I give this book three stars instead of two. Truthfully, it is probably a 2.5 star book.

An example of the authors' inconsistent narrative style is this: Chapter two goes into great detail on the obvious - clamping, antialiasing, and the brick wall texture. In chapter 15 on "Fractal Solid Textures", the authors brush over the complex issue of how to produce fire, water, wind, and rocky terrains. Also, the vast majority of the time, rather than show the procedural modeling with pseudocode or with a high level language such as C, the authors choose "Renderman", which is unfamiliar to many people and makes the included code useless to those uninitiated in that language. Plus, in many cases Renderman has functions that hide the details of particular algorithms. This is counterproductive, since the algorithms are supposed to be the point of this book in the first place, or at least I thought that they were.

My advice to people interested in this subject is to skip this book unless you can find it at a greatly reduced price and look online at Elias Hugo's webpages on procedural modeling. Mr. Hugo explains the authors' techniques much better than the authors themselves do.

... one might note that this book is developed in such a waythat makes it quite modular. At first Wangsness develops an examplecompletely, often leading to daunting equations. This is wonderful. However if you want to pick and choose a few key assumptions, and developed a more specific case, you can do that with Wagness' help, as well.

Some of the problems are tedious, and void of instruction. Oftentimes, one has to result to digging through the chapter just to find the correct equation, leaving you with no physical intuition of what is really happening. If a professor drew up their own problems to accompany this text, you'd definitely have a winner. END

OK, OK... so Griffiths is a very good text. I believe this book is better, having read both. Overall, 'EM Fields' is very well written, providing a strong background in vector calculus to bolster the topics that follow. I agree with the other reviewer who writes that explanations are based on mathematical rather than physical arguments. However, I find this style easier to understand. I do not believe that this formalism detracts from an overall grasp of the material, provided that physical intuition is used as well.

This book is indeed very modular, if you have any previous EM training and the required mathematical skills you won't have any difficulty using this as a practical, working reference. As a consequence of the modularity, there is some repetition of the information but it's a small price to pay for the completeness of the individual modules.

One of my favorite features of the writing is the clear references to previous results making it easy to review the references (and completely eliminates any need to search the index). I far prefer this to the usual method to make only vague references to previously developed concepts and is one reason why I find this is a good reference work.

Overall, the level is more advanced than Cook though better written. Some of the development of the material is rather novel (e.g., Amperes Law) and considerably more approachable than corresponding works by Smythe (ugh), Peck, or Stratton. I recommend Feynmans lectures in addition to this book. I find the two complement each other quite nicely.

I believe there are basically two breeds in the world of EM textbooks. One is obviously J.D. Jackson and the other E.M. Purcell. If Griffiths follows Purcell's approach, I'd say Wangsness is in the style of Jackson (of course no direct comparison is possible, Jackson does not really discuss statics anyway).

Wangness is very much _detailed_ and provides ample examples, many of them kindly worked out. I am not sure if this book provides strong background in vector calculus, though. I always had troubles getting some geometrical intuitions. I guess I have learned more from Purcell in this respect.

Of course, there are many other great books such as Lorrain/Corson, Feynman volume 2 and such. Should be nice to look at those as well.

If you wanna master Jackson's classic bible, this is absolutely a prerequisite!!.
Most people love Griffith, but this is more than it.
Some people complain about this book which is too mathematical, but math is the language of E&M. Without strict, precise math, you gonna get nothing from E&M.
This book, I bet, will solidify your all needed mathematical background to conquer Jackson's Classical Electrodynamics.
Specially, the concept on conductor is explained very well with very nice examples in Ch.6 and dielectrics in ch.10 is well treated.
Useful and powerful solved examples are available on the right place.
The only not well treated topic is a radiation part, but Griffith will compensate for this.
Again, I'll strongly recommend this book for anyone who will continue graduate study in physics, whatever he will major.