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Paradigms of AI Programming is the first text to teach advanced Common Lisp techniques in the context of building major AI systems. By reconstructing authentic, complex AI programs using state-of-the-art Common Lisp, the book teaches students and professionals how to build and debug robust practical programs, while demonstrating superior programming style and important AI concepts. The author strongly emphasizes the practical performance issues involved in writing real working programs of significant size. Chapters on troubleshooting and efficiency are included, along with a discussion of the fundamentals of object-oriented programming and a description of the main CLOS functions. This volume is an excellent text for a course on AI programming, a useful supplement for general AI courses and an indispensable reference for the professional programmer.
One of the Best
| Customer Rating:  | | "Paradigms of Artificial Intelligence Programming" is one of the best books of computer science that I have ever read. I put it up there in the pantheon with "Structure and Interpretation of Computer Programs". I have found more useful and mind expanding material in these case studies than I have in many other books on computer science. I highly recommend this book to anyone, even if they have never used Lisp. |
Norvig's Corollary to Greenspun's Tenth Law of Programming
| Customer Rating: | This book has been called "The best book on programming ever written". I'd have to agree--it is certainly the best that I've ever read.
William Zinsser said, "The essence of writing is rewriting" and the same can be said for writing computer programs. Norvig's book presents this process--how the limitations of a program are overcome by revision and rewriting. What sets Norvig apart as a writer is that, amazingly enough, he can write about debugging (the most dreaded part of computer programming) and make it a fascinating read!
Lisp has been getting a higher profile lately because of essayists like Paul Graham and Philip Greenspun; in particular, Greenspun's Tenth Rule of Programming which states: "Any sufficiently complicated C or Fortran program contains an ad hoc, informally-specified, bug-ridden, slow implementation of half of Common Lisp." So, should this book be read as an exhortation to return to Lisp as the preferred programming language?
Paradoxically, I think not. One third of the way through the book, Norvig shows us how to implement Prolog in Lisp. From then on out, most of the AI techniques he presents either directly use Prolog instead of Lisp (such as his excellent discussion of natural language processing using Prolog) or use Prolog as a base to build on (such as his discussions on knowledge representation).
From this we can abstract what I'd like to call Norvig's Corollary to Greenspun's Tenth Law of Programming: "Any sufficiently complicated LISP program is going to contain a slow implementation of half of Prolog". I'm leaving out the "ad hoc", "bug-ridden" part of Greenspuns's law, because Norvig's programs are neither. But it is quite remarkable the degree to which, once having absorbed Prolog, Norvig uses Prolog as the basis for further development, rather than Lisp.
Is this a book about Prolog then? Again, no. What is the take-away message? It is this: as our world becomes more and more complex, and as the problems which programmers are facing become more and more complex, we have to program at a higher and higher level.
Norvig does not stop at just embedding Prolog in Lisp. He also shows us how to embed scheme as well. Excellent discussion on the mysterious call/cc function and on continuations.
In a capsule review, it is impossible to really give an overview of a 1,000 page book like this one. But the scope and heft of the volume really needs to be commented on: the programs presented in this book are like basis vectors, the totality of which nearly span the space of programming itself. In no way should this be considered "just an AI book" or "just a LISP book". This book transcends language, time, and subject matter. It is a programmer's book for the ages. |
An Excellent Reference on WHY to write good Lisp
| Customer Rating: | | This book is equally excellent regardless of whether you wish to regard it as: a) A historical study of Artificial Intelligence, with USABLE examples of code, or b) A book presenting techniques for programming in Common Lisp. As a reference about Common Lisp, it is certainly lacking, but this is no great problem when both the Common Lisp HyperSpec and Steele's book are readily available in electronic form. It provides something more important: SIGNIFICANT examples, and significant discussions on WHY you would use various Lisp idioms, and, fairly often, discussions on HOW pieces of Common Lisp are likely to be implemented. Its discussion of an implementation of the LOOP macro, for instance, provides a very different point of view than the "references" to LOOP. (Contrast too with Graham's books, which largely deprecate the use of LOOP.) From an AI perspective, it is also very good, providing WORKING SAMPLES for a whole lot of the historically significant AI problems, including Search, PLANNER, symbolic computation, and the likes. It would be interesting to see parallel works from the following sorts of perspectives: - The same sorts of AI problems solved using functional languages (e.g. - ML, Haskell), to allow contrasting the use of those more modern languages. Being more "purely functional" has merits; such languages commonly lack macros, which is something of a disadvantage. - The use of CL to grapple with some other sorts of applications, notably random access to data [e.g. - databases] and rendition of output in HTML/SGML/XML [e.g. - web server]. |
Not advanced, but good and vast
| Customer Rating:  | | The strength of this book is its combination of breadth and completeness: there is working code (well beyond the toy stage) of a large number of different AI systems that cover a large subset of what is commonly considered AI. The programming itself is rather basic, and very straightforward. In many places an advanced programmer would have avoided a global variable, unified code through the use of higher-order functions, had functions communicate through a shared local environment, created a lazy list, you name it. The author avoids most of these more advanced approaches in order to present the ideas behind the approaches without being sidetracked into programming technique issues, and that is the correct choice for this book. Even as it is, there is already the duplicity of teaching Common Lisp and teaching AI programming. That being said, the code in general is not bad at all, even though I wouldn't want my students to learn CL programming from it. The author has simply bent down to the level of, a good C programmer, and worked from there. His main intention being to teach AI programming approaches, he has spent much less time to raise the programming level of his audience. Knowing the author's level of Lisp programming, I can't wait to see a book by his hand on how to use abstraction as an organising principle in programming. |
Excellent study of both AI and Common Lisp
| Customer Rating: | | I have no background in computer science or AI, but found myself needing to use Lisp for various creative and artistic purposes. I've spent a lot of money on books relating to Common Lisp, but I wish I had just gotten this one and Touretzky's "Gentle Introduction to Symbolic Computation." The particular strengths of this book are its detailed discussion of advanced topics, especially optimization, and the practical overview of current and historical AI topics through programming examples. Very clearly written. |
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