Product Description

The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.

Customer Reviews (16)

Good Book
I am currently using this book for an Artificial Intelligence (AI) course at Duke University. I purchased the book because it was required for the course, and have been pleased with it thus far.

The book is well written and very comprehensive. It does not go into great detail with the various topics in AI, but it does give a very thorough overview of methods being used. It appears to be very up-to-date with the subject matter. Also, it is not programming language specific, which was great for me because my java and C are a bit rusty.

It is a bit pricey, but no more than other well written text books. I would recommend this book to anyone looking to get into or to teach a course in AI.

Exactly as expected
I bought this book and very promptly received it as expected.I have no complaints and look forward to learning the material.

Well written
I am about halfway through this book for a class on Artificial Intelligence. One thing that really sticks out about this book is the writing style. I have much respect for authors who use plain English and don't sandbag the reader with needlessly complex language. All of the concepts are quite technical (in my opinion) yet I have no problems understanding the concepts because of the writing style. There is a certain clarity to it.

As for the overall merit, I'll withhold judgement and complete the review after I'm finished with the book.

Finally, a text book that you can read
Text books are usually cryptic and boring, but this one's actually quite fun to read. It's so easy and fun that I'm actually excited when the professor assigns a new reading. In fact, I liked it so much that I looked up the author to find more of his books, and guess what? The author works at Google. Someone in Google making a user-friendly textbook? I'm in!

Poor learning tool
I'm finishing up my CS Master's and this is one of the most confusing and opaque books I have had to deal with.Everything is overly complicated, poorly explained and lacking in examples.We will work through problems in class that are as easy as adding up some numbers, and the book will take 4 pages and lots of unnecessary information to make the point.The authors are more focused on creating a comprehensive encyclopedia of AI than making something that students can learn from. ... Read more

Product Description
The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.Amazon.com Review
Artificial Intelligence: A Modern Approach introducesbasic ideas in artificial intelligence from the perspective ofbuilding intelligent agents, which the authors define as"anything that can be viewed as perceiving its environmentthrough sensors and acting upon the environment througheffectors." This textbook is up-to-date and is organized usingthe latest principles of good textbook design. It includes historicalnotes at the end of every chapter, exercises, margin notes, abibliography, and a competent index. Artificial Intelligence: AModern Approach covers a wide array of material, includingfirst-order logic, game playing, knowledge representation, planning,and reinforcement learning. ... Read more

Customer Reviews (87)

All theory but lacks concrete examples
The book explains well the theory behind many AI techniques, but you only reaches the pseudocode, so people that are new to programming must resort to Google to get some better examples and some down-to-earth approaches if you want to implement your AI

I Confess, I Wikipedia did a better job explaining some of the concepts...
This was a decent book, but really, I felt the authors took a simple principle and DRAGGED it through the mud until it was no longer simple. A quick search online often found something that was much more consumable and concise.

Could have been great, but ...
As some reviewers have said, this is probably the most comprehensive AI textbook on the market. The "pros" of the book have been covered pretty well by other reviewers, so I'll limit my review to some of the things that bug me about the book.

1. No answer key for any problems. This feature has been standard in textbooks for decades as a way for students to self-check their understanding of the material.

2. Examples are scant and sometimes stop in the middle. For example, in Chapter 13, the example of applying Bayes' Rule gives one approach and indicates that it will discuss an alternative approach, but then the text just goes off on another path and never completes the example.

3. Inconsistent and (sometimes) convoluted pseudocode for the algorithms. Pseudocode should be a fairly-close-to-English approximation of the algorithm, but this book seems to mix RTL, English, and any other notation. Though the appendix includes an attempt at explaining their rationale behind their own brand of pseudocode, it's incomplete at best. Also, the function names don't follow any convention I've ever seen (I have 30+ years experience in software), and aren't even consistent within the book.

4. Condescending language. This should never occur in a textbook. In far too many places, the authors tell us that "the sharp-eyed reader will have noticed" or similar phrases, which basically implies, "if you didn't get our explanation and find the hidden subtext, you are not sharp-eyed". All such language should have been edited out.


The authors came so close to writing a classic, but sadly missed the mark. I think that any professors who claim that their students "universally love this book" are deluding themselves. Still, if your professor is good at explicating the material, it's worth going through it once, then switching to other materials, maybe primary source materials in the subfield(s) that grab your interest.

Nice introductory text on AI
I used this book for a graduate course in Artificial Intelligence. We covered about half of the book in class. The book is very comprehensive and I found that parts of the book have heavy notations including calculus (and I needed to review some of those concepts in order to follow completely). Overall I liked the book very much and I highly recommend to those who are looking for an introductory and broad view of AI.

cheating
This seller is cheating on the item he is selling. The book he sold to me is an international edition and does not have the same cover as list above. Do not buy things from the seller. ... Read more

Product Description
UNDERSTANDING ARTIFICIAL INTELLIGENCE is one of the first four titles that launch an exciting new Pocket Science series, from the editors of America's leading popular science magazine, Scientific American.

Comprised of critically acclaimed essays by the world's leading experts on each topic in the series, these collections will become definitive texts on crucial issues of our technological times. The authoritative and prestigious reputation of Scientific American puts these books at the top of any science fan's list.

Called AI by followers and practitioners, the field of Artificial Intelligence is dedicated to the proposition that human brains are nothing more than machines, albeit extremely complicated ones, whose abilities will someday be duplicated-and surpassed-by computers.

This collection of essays discusses the wide spectrum of knowledge compiled on the pursuit of this elusive goal. It includes a fascinating overview of the subject by Douglas B. Lenat, the president of Cycorp, Inc., and a forward-thinking essay on "The Rise of Robots" by Hans Marvec, the principal research scientists at the robotics Institute at Carnegie Mellon University, which conservatively estimates that by 2050, robot brains based on computers will start rivaling human intelligence.

Other articles include "Here's Looking at You," which profiles a robot who learns about itself and its environment through trial and error, as well as a profile on Marvin L. Minsky, the mastermind behind Artificial Intelligence. The book-like the entire series-is targeted to intelligent readers who want to expand their understanding of complex scientific subjects and contains essays from top scientists working in the field. Like the magazine, the book encompasses a spectrum of innovation through expert-authored articles that demonstrate the convergence of science, technology, and the world economy, challenging readers with fresh, new ideas and empowering them to make smart, strategic decisions. ... Read more

Customer Reviews (2)

Required reading for 21st century humans!
"Will robots inherit the Earth? Yes, but they will be our children."--Marvin L. Minsky

"Understanding Artificial Intelligence" is a great little book (139 pages, paperback). It's one of the wonderful "science made accessible" series by Scientific America's editors.

The book is a compilation of excellent essays by key thinkers in the field. Don't be scared off if you don't have a degree in computer science. All entries are well written and not so heavy as to lose most readers.

This book is a short read but it will stay with you for a long time. If you plan on being alive to see the next few decades, you need to know something about artificial intelligence. This book is a great place to start your education.

The editors write:

"Will a future proclamation be necessary to free artificial intelligence [from human bondage]? Should we allow this to happen? Should we fear out electronic offspring? Will ambulatory AI machines proceed down the Terminator's path . . . or down the benign road become helpful human assistants? Will artificial humans inherit the planet, as some scientists are now inclined to say, or will the melding of biology and bionics simply necessitate a new definition of human? We may not have all the answers yet, but the questions will become more important as each new invention leads toward true artificial awareness."

I highly recommend this book. It educates, yes, but more important, it inspires a sense of wonder and excitement about what tomorrow may bring.


--Guy P. Harrison, author of Race and Reality: What Everyone Should Know About Our Biological Diversity" and "50 Reasons People Give for Believing in a God" (a skeptical analysis of common justifications for religious belief)



The following is a column about robots and AI, published in the Cayman Observer on Sunday in April 2010. If you find it interesting, then you will love "Understanding Artificial Intelligence."


Will robots and AI rule tomorrow?

I am never alone. I share my Grand Cayman home with three humans, two dogs, one cat, and two robots. A few times per week my mechanical friends sweep the floors throughout my house. They navigate around chairs, scurry under tables, and annoy the cat. The more advanced model knows when it's had enough and returns to its docking station to nestle in for a recharge.

This is all very important to me because it means I don't have to sweep. While the robots work, I am free to engage in activities far more appropriate for a member of the most intelligent species on Earth--like watching TV.

Robots have plans that extend far beyond mere housework, however. Soon they will be everywhere. But there is the slight possibility of a downside--extinction of the human species. Yes, intelligent machines in the not-so-distant future may become so smart that they could threaten our existence. My cute little floor sweepers may turn out to be the great-great grandparents of real-life "terminators" that will kill us all one day.

Just like any other normal Cayman family, my children and I often discuss the impending robot apocalypse. My son reassures me that robots won't have any need to fight us because we will eventually be machines just like them. We will become robots, he believes. Given recent advances in prosthetic limbs, ear implants, brain implants, and so on, he may be on to something. Maybe we will merge with our technology so intimately and thoroughly that there will be no "us" and "them" to define battle lines. My daughter is not worried either. She is convinced that someone will be smart enough to remember to simply program the robots to be nice. Ah, don't you just love youthful optimism?

Still, I wonder. With computers on course to become freakishly powerful in about three or four decades, and with robotics development in high gear, will we be able to hang on to civilization's top rung? It seems likely that a game-changing new "species" is on the horizon and approaching fast, one that will be difficult if not impossible for us to control. Thanks in large part to unprecedented military investment in robotics, we are now stepping into a very different world--for better or worse. "In the blink of an eye," writes Peter Singer in his book, "Wired for War", "things that were just fodder for science fiction are creeping, crawling, flying, swimming and shooting on today's battlefields. And these machines are just the first generation of these new technologies, some of which may already be antiquated as you read these lines."

Hugo de Garis, an artificial intelligence researcher as well as my pleasant Face Book friend, may be engineering our collective doom. He is the author of the nightmare-inducing book, "The Artilect War," in which he admits feeling conflicted about his work. He believes it is highly probable that super-intelligent machines will brush us aside one day. Despite those fears, however, his research is so fascinating that he can't stop himself.

Unprecedented transformations are occurring right now. For example, did you know that in 2009 the United States Air Force trained more ground-based "pilots" to fly robot planes than it did traditional pilots for conventional planes? This year, the Air Force is projected to acquire more new robot planes than new conventional aircraft. This represents a monumental shift in the human-robot equation, yet the public mostly doesn't know or doesn't care. The various military robots that we know of are controlled and monitored closely by humans today, but what about tomorrow? Robot autonomy on the battlefield will be here soon, if it isn't already.

The military, rather than my floor-sweeping needs, is driving much of the cutting edge research. So much so that when the final histories of the wars in Iraq and Afghanistan are written one day it is possible that surprisingly little attention will be given to Bush, Saddam, the Taliban, oil, and terrorism. The greatest impact of these wars may well turn out to be robots.

I attended an exhibition of advanced and near-future technology called "NextFest" a few years ago in Chicago. I spoke with a representative from the company that makes one of the drones used by the US Air Force. I met a solider who wore a sleek prototype suit that, when fully developed, would make him stronger and even tighten automatically like a tourniquet to slow blood loss if he was wounded in battle. A Japanese woman demonstrated how strong she was thanks to the robotic "exoskeleton" she wore. I saw ASIMO, the famous Japanese robot, do its usual slow shuffling walk. Interested but not overwhelmed, I felt like I was watching the Australopithecus of robot evolution. But, of course, the robot equivalents of Homo erectus and Neanderthal are already being designed or built somewhere right now. There will be no four-million-year-wait for them. Don't blink.

I am not suggesting that anyone should panic or lose sleep over a possible robot takeover in the future. At the very least, however, you should be aware of what they are up to. The robots are not coming; they are here already. The invasion has begun. I know because an indifferent little robot on a mission just rolled by in front of me right here in my living room. It cares nothing about me; it just wants to sweep. That's what it does; that's who it is. I admire its dedication and focus. But I wonder, will the day come when its descendants demand more?

Mind-Children and Smart Refrigerators
Understanding Artificial Intelligence is a collection of articles about artificial intelligence that have appeared in Scientific American over the past decade. Together they show AI as a fascinating and integrated field, rather than just a series of isolated projects. The authors, without exception, are using the human mind as an inspiration for creating superior technology. They are impatient with the idea that they are trying in any way to create 'articial humans'.

All the authors are well-known AI experts who have put in their time at the lab bench - or computer keyboard - and are talking from hands-on experience. Every piece meets Scientific American's standard of good, clear English without `talking down' to readers. The enthusiasm and pragmatism of these scientists comes through clearly.

At around 150 pages, this e-book was easy to read in one sitting, a perfect length for a domestic flight. ... Read more

Product Description

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.

Customer Reviews (8)

Amazing book about designing programs
Don't let the title of the book fool you: Yes, it presents all its code in Common Lisp and yes, the domain it discusses mostly is Artificial Intelligence, but PAIP (as it's affectionately called by fans) is a book about the general process of designing programs and implementing them. It's just a by-product that along the way you will learn Common Lisp (which is a very interesting language) and will get familiar with some very interesting problems in the fields of AI, code optimization, search, compilation and OOP/

Peter Norvig is a masterful programmer and writer. His code is excellently thought-out and designed, and shines with originality and clarity at every snippet you read. Every chapter has interesting insights and great code in it. Reading through this book from cover to cover is a behemoth task, but even starting small is great. Norvig even includes several exercises *with solutions* for each chapter, which really helps understanding the material.

In short, PAIP is one of the best books about programming and computer science I have ever read. It is highly recommended.

One of the Best
"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
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 "justa 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
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
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. ... Read more

Product Description
Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques.

"Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games).

* The first comprehensive, professional tutorial and reference to implement true AI in games written by an engineer with extensive industry experience.
* Walks through the entire development process from beginning to end.
* Includes examples from over 100 real games, 10 in-depth case studies, and web site with sample code. ... Read more

Customer Reviews (2)

Excellent and approachable
The vast majority of software development books, whether it be for line-of-business app dev or game development, seem to have little to no information that can be found via a casual internet search.

This book is one of the few exceptions.There is a refreshing breadth and depth of game AI knowledge in this book that has been of tremendous help.Unlike the common "Gems" series of books, this book contains enough information on nearly every topic for the reader to build a 'ground up' implementation of their own.

My only complaints are that the pseudocode seems to be overly simplified and not as easily converted to a concrete implementation as I'd like, and that even for a book on game-specific AI implementations, the authors seem to enjoy a bit more of an academic/idealized approach to the design.That might be less bothersome to a professional game developer, but I'm at the hobbyist/indie level, and sometimes need a quick-and-dirty implementation before I begin to really understand what's going on.

Having said that, I was able to use the book to learn about and implement goal-oriented action planning, fast and flexible A* path finding (with additional info on modified funnel algorithm online), and several other critical components.

I would absolutely recommend this book.

Detailed explanations of AI algorithms, their purpose and usage
Artificial Intelligence for Games by Ian Millington and John Funge covers lots of topics but is mainly designed to help the reader to master one element of game development which is artificial intelligence (AI). The book covers a wide range of techniques for game AI including detailed explanations of AI algorithms, their purpose and usage.

As I have learnt from this book, artificial intelligence is about making computers able to perform some thinking tasks that human and animals are capable of. This includes superhuman abilities in solving many arithmetic, sorting, searching and decision making problems. This book shows how it can be achieved revealing a range of techniques to the reader.

The book is split into five parts: introduction for AI in games, the substance of the AI (movement, pathfinding, decision making, tactical and strategic reasoning, learning), technologies and ways of implementation that enable the AI to do its job and finally designing game AI.

I think this book could be aimed at a wide range of readers but is most suitable for those looking for solid understanding of game AI and comprehensive reference to techniques used in top studios. The book helps to gain a deep and thorough view on modeling complex emotional states, triggers, and behaviors. To get the most from the book, you have to manage some time to read it and to understand its contents. If you need a quick AI solutions repository you should probably find another book related to a particular technology or computer language.

The book is associated with a website that contains a library of C++ source code covering the techniques found in the book. Hopefully the C++ code used in samples is relatively easy to read and includes many comments. There are also demonstration programs compiled as EXE files.

Besides many technical solutions to AI related issues I have also learnt from this book a few high-level things. For instance I have learnt that creating good AI is all about matching the right behaviors to the right algorithms and that often, a very simple technique used well can have better results then implementing complex the AI in the game.

This book is an open minder or a view broadener on many aspects related to the AI in games. It can also serve as a great example of good analysis, desing and prototyping examples of more or less complex algorithms which are about to use in specific projects. This is a very valuable title for any computer science professional dealing with Artificial Intelligence (for games). ... Read more

Product Description
The Connection Machine describes a fundamentally different kind of computer. It offers a preview of a parallel processing computer that Daniel Hillis and others are now developing to perform tasks that no conventional, sequential machine can solve in a reasonable time.

W. Daniel Hillis is a founder of Thinking Machines Corporation where he is engaged in building connection machines as a significant step toward real thinking machines. The Connection Machine is included in the Artificial Intelligence series, edited by Patrick Winston, Michael Brady, and Daniel Bobrow.Amazon.com Review
This book is essentially an edited version of Hillis'slandmark thesis describing the design and implementation of theConnection Machine (CM), a massively parallel computer. The philosophybehind the CM's design is that the right kind of machine for manyimportant computational tasks is a machine with vast numbers of simpleprocessors doing the same thing on different data. This notion of oneprocessor per important data element (one processor per pixel in imageprocessing) is inspiring.

The Connection Machine is not atextbook and may be intimidating to beginners, but it provides awonderful picture of the kinds of issues involved in designing a newmachine. The book is well written and features a host of interestingdiscussions by Hillis on related topics (such as general philosophy ofparallel computing). Anyone interested in the subject of computerarchitecture will enjoy and profit greatly from this book. ... Read more

Customer Reviews (3)

Connection Machine? Count me in!
This book is great. I have loved computers for years, and this book has given me a completely different way to think about them.

Hats off to Daniel Hillis!

-n8

easy reading, good intro to massive multiprocessing
Especially given that this book is in fact a doctoral dissertation, it's extremely easy to read.This is not to say that it is written for children, but rather, the author has used language well to convey concepts rather than to confuse and sound stuffy.

The book states the limitations of the traditional Von Neumann computer architecture (which by and large we are still stuck with today) and then goes on to explain how an entirely different approach with many processors could work.

What do you get when you connect a zillion computers togethe
This reference describes a computer architecture containing thousands of processor/memory cells that can be connected together by software, and the rational behind this architecture. It is easy to read, and is useful in providing the general reader with a feel for large multiple processor computation, in particular an architecture well suited for semantic network marker propagation. ... Read more

Product Description
Recent decades have witnessed the emergence of artificial intelligence as a serious science and engineering discipline. Artificial Intelligence: Foundations of Computational Agents is a textbook aimed at junior to senior undergraduate students and first-year graduate students. It presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents. By showing how basic approaches fit into a multidimensional design space, readers can learn the fundamentals without losing sight of the bigger picture. The book balances theory and experiment, showing how to link them intimately together, and develops the science of AI together with its engineering applications.Although structured as a textbook, the book's straightforward, self-contained style will also appeal to a wide audience of professionals, researchers, and independent learners. AI is a rapidly developing field: this book encapsulates the latest results without being exhaustive and encyclopedic. It teaches the main principles and tools that will allow readers to explore and learn on their own.The text is supported by an online learning environment, AIspace, http://aispace.org, so that students can experiment with the main AI algorithms plus problems, animations, lecture slides, and a knowledge representation system, AIlog, for experimentation and problem solving. ... Read more

Customer Reviews (1)

A "neo-classical", logical approach to AI
This is really a "2nd edition" of their book by a different name and publisher:"Computational Intelligence - a logical approach" (1998, Oxford, minus one co-author), with some new material.

It's a very good introductory AI book, similar to AIMA, but with a focus on logic-based AI.I haven't read the new book in detail only because I use exactly the same approach in my AI R&D.

In particular, probabilistic reasoning in logic-based AI is explained here.

Logic-based AI fell out of favor in the 90s, being eclipsed by connectionism and statistical learning.But I think it can have a revival, partly thanks to the new popularity of Bayesian networks.The Semantic Web is also logic-based. ... Read more

Product Description
New approaches to artificial intelligence spring from the idea that intelligence emerges as much from cells, bodies, and societies as it does from evolution, development, and learning. Traditionally, artificial intelligence has been concerned with reproducing the abilities of human brains; newer approaches take inspiration from a wider range of biological structures that that are capable of autonomous self-organization. Examples of these new approaches include evolutionary computation and evolutionary electronics, artificial neural networks, immune systems, biorobotics, and swarm intelligence—to mention only a few. This book offers a comprehensive introduction to the emerging field of biologically inspired artificial intelligence that can be used as an upper-level text or as a reference for researchers.

Each chapter presents computational approaches inspired by a different biological system; each begins with background information about the biological system and then proceeds to develop computational models that make use of biological concepts. The chapters cover evolutionary computation and electronics; cellular systems; neural systems, including neuromorphic engineering; developmental systems; immune systems; behavioral systems—including several approaches to robotics, including behavior-based, bio-mimetic, epigenetic, and evolutionary robots; and collective systems, including swarm robotics as well as cooperative and competitive co-evolving systems. Chapters end with a concluding overview and suggested reading.

A teacher's kit with slides and exercises is available online at http://baibook.epfl.ch/ ... Read more

Customer Reviews (1)

A very cohearent covering of a large territory understandable even to a layperson
www.gabrielfalco.com
Concepts detailed in this text have become pillars of my thinking. Every year I purchase several textbooks to educate myself on topics that interest me. Bio-Inspired Artificial Intelligence balances delivering conceptual detail with real world integrated examples to aid in deep and successful comprehension of the topics. The text answers questions, informs and prompts one ask broader questions. Incredibly, it is actually very enjoyable to read; I think this may have to do with the good writing.
... Read more

Product Description
This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book. ... Read more

Customer Reviews (2)

Plain simple English!
I think this book is great! It explains the fundamentals of AI in a way that is easy to read and understand! I recommend this book to AI newbies who don't want to spend hours figuring out technical language. It was really useful for me!

Best AI book I've seen so far
I am just getting into AI and I've been looking for some good AI books. This is the first one I've found that covers a great selection of AI topics and talks about them in PLAIN ENGLISH instead of trying to baffle you with lots of academic gibberish! It's also liberally sprinkled with clear diagrams and programming code. So if you want a practical AI book you can actually use and understand, I think this is a good one. It's written by an AI professional who can actually WRITE and communicate clearly! What a surprise!

... Read more

Product Description

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

* An evolutionary approach provides a unifying theme
* Thorough coverage of important AI ideas, old and new
* Frequent use of examples and illustrative diagrams
* Extensive coverage of machine learning methods throughout the text
* Citations to over 500 references
* Comprehensive index ... Read more

Customer Reviews (15)

Good general overview
The field of artificial intelligence has an interesting history, both in terms of its content and the philosophical debate it has provoked. The field could also be loosely described as divided into two camps, those who view it as a collection of highly sophisticated algorithms, and those who view it as an attempt to create machines that exhibit human-level intelligence. Ironically, in the latter camp, it is difficult to assess the progress that has been made, since criteria for measuring machine intelligence are never explicitly given. Instead, dependence has been made on the "Turing test" for intelligence, a test that is difficult to apply, and in fact can be said to be too vague for a practical, objective assessment of machine intelligence.

This book is written more in the context of the latter camp, than in the former. However, in-depth discussion of the Turing test is not given, and this actually is one of the main virtues of the book, although the author clearly believes that the purpose of doing research in artificial intelligence is to achieve human-level intelligence. As he remarks in the last paragraph in the book, it was written to overview the techniques that he believes are required to achieve human-level intelligence. Although he does not explicitly give the reader tests for machine intelligence that will allow progress to be measured, he devotes a small portion of the book to various ideas on just what constitutes intelligence.

The book also gives a general (and sometimes very brief) overview of the algorithms used in artificial intelligence.Search heuristics, neural networks, and genetic programming are some of the topics that are covered. The influence of the "intelligent agent" paradigm, that is now taking the AI community by storm, is very apparent throughout the book. The author though does not neglect some of the topics in "good-ole-fashioned" artificial intelligence that arose decades ago and is still applicable today, especially in the field of logic programming. These topics include resolution in both the propositional and predicate calculus, and in expert systems. By far the best discussion in the book is on knowledge-based systems and evolving knowledge bases. This topic has taken on considerable importance in recent years due to the importance of data mining and business intelligence.

Readers who are considering artificial intelligence as a career choice will find good motivation by reading this book. The field also is quite different than most others in that it respects a high degree of individual creativity and ingenuity, and has a high bandwidth for new ideas. Beginning with its origins in the 1950s, the field has grown by leaps and bounds, but its applications have exploded in the last five years, fueled mainly by business and financial applications. Concerned not only with achieving human-level capabilities, but also with other forms of intelligence and how they can be useful, artificial intelligence has become one of the predominant forces in the twenty-first century. One can only be excited and optimistic about its further advances.

Run Forrest Run
In general avoid this book.
I purchased this book for a course, and unfortunately this is my first book. Its 95% maths, of course AI is a lot of math, but the book is so abstract and nothing related to practical stuff. Take convolution filters, it gives integrals and all that stuff, but what exactly does it do, how does it perform it on images, and where the heck are sample images, and sample matricies.
I bet this author must have sent this book out to teachers so that 50 students would have to buy this over priced book with no practicle use and so hard to read/understand and extremely dense.

Not a good intro to AI
While the book is well organised and number of topics covered is substantial, this was the worst intro-to-anything book I had to suffer through. If calculus is something you are very comfortable with, then go ahead, read it. :-)

nice, but with these errors
A nice book. Especially the order in which the topics are covered is a good idea. However, you will not find the following errors reported in the book's webpage:

Page 52: The "high-degree function" is not a function!

Page 92: In Figure 6.6, the topmost pixels that get deleted as a result of the averaging operation should actually remain there, since both their sums are 4, which is greater than the threshold, which is 3.

Page 100: In Fig. 6.13, the last row of the last image contains a spurious image boundary.

Page 151: In Fig. 9.8, there are two nodes with name n; the one which is higher in the figure should have the subscript 1.

Page 152, item 3 in the list: There is an implicit assumption that h-hat always returns 0 for goal states. I don't think that this assumption is stated earlier in the text.

Page 165: In Figure 10.1, all arrows are supposed to be pointing away from the current state.

Page 246: The last paragraph mentions ".. the two interpretations for Clear and On suggested by Fig. 15.2", but aren't actually THREE interpretations suggested for On?

And in the current errata list in the book's website, something is clearly wrong with item 6, since it says n_i should be replaced by n_i.

All in all, a good book.

Varies between being superficial and incomprehendable
After having borrowed and read part of Nilsson's previous book "Principles of Artificial Intelligence" at the library some years back I was quite positive about the prospect of reading this one. However, it falls short on many of my expectations and can therefore not be recommended for neither the beginner nor the expert.

The book covers all the major areas of artificial intelligence but does so in a very superficial manner. There isn't actually enough information in the book at allow to to implement some of the techniques available - it is mostly teasers. Also many of the subjects are - and even some of the subjects that I already knew about beforehand - incomprehendable and I often got more confused about a subject than before I began reading it.

I very rarely give a book one star, but this one deserves it in the light of the many better books on AI. I recommend that you read "Russell and Norvig: Artificial Intelligence - A Modern Approach" instead.

Jacob Marner, M.Sc. ... Read more

Product Description
Can machines really think? Is the mind just a complicated computer program? "Introducing Artificial Intelligence" focuses on the major issues behind one of the hardest scientific problems ever undertaken. Artificial Intelligence is not just a fictional concept. Half a century of research into the construction of intelligent machinery has resulted in machines capable of beating the best human chess players and humanoid robots that can walk and interact with us. Despite early claims that intelligent machines were just around the corner, progress has been slow and difficult. Consciousness and environment are tow of the deeply complex problems are two deeply complex problems encountered. How exactly should we go about building an intelligent machine? Should it work like a mind? Should it work like a brain? Does it require a body? "Introducing Artificial Intelligence" clearly explains the advances made over the past half-century, from Alan Turing's influential groundwork to cutting edge robotics and the New Al. ... Read more

Customer Reviews (7)

Amazing Book!
This was the first real book I read on the topic of Artificial Intelligence, and I must say...the best.This books topics are not outdated at all, it completely applys to current studies.This is an amazing book for a good introduction into the topic, and mainly covers the philosophical side of creating intelligent and conscious artificial beings; explaining all sides of the issue in a incredibly information pakced and detailed cartoon format.A very good book, after reading it twice I finally understood the underlying principles of AI.If your interested in Ai I'd also recommend the other Introducing book on Consciousness, which gives a detailed description into the materialist, dualist, and mysterian views on consciousness and the formation of a theory of conscioussness, whos philosopical ideas is realted to AI.

Not a technical introduction...
This book is not a technical introduction to AI.The book is targeted at people with no technical or computing expertise, and does not have enough depth to be of value to anyone interested in AI from a technical angle.

That said, it would be great as an introduction to someone like my wife (a nurse).

I wish I had read the reviews on this book before purchasing it, but I did get to look at the cool drawings in this one!

An introduction of an introduction
This book is intended for a young audience... Avoid buying it in case you take the subject seriously. On the other hand, if you just want to have an overall idea of what IA is, it's ok.

Thought, Consciousness and Understanding (oh my!)
This is a very light weight read on the subject that discusses the history of the slow and not certain advancement of the concept of what Artificial Intelligence is or will be.

As a person that is new to the subject I enjoyed the format -- lots of illustrations.

I was amazed to learn how inter-disciplinary the topic is. The book draws from the perspectives of psychology, mathematics, computer science, biology, and philosophy.Before starting the book, I was personally hoping to get an introduction to computer science tools (neural networks, Bayesian network etc.) that make up modern AI.However, I believe I am better off for starting with a book that helped me better understand that there is more to AI than computer science.

Yet another fascinating book in the "Introducing..." series
Coming from a Computer Science background, but only having been exposed to AI via science fiction, the most interesting thing I learned while reading Introducing Artificial Intelligence was the distinction between the two major schools of thought in AI research:"strong AI," or those who believe machines can be made to think like humans or better, and "weak AI," those who seek further knowledge about natural intelligence through the use of artificial simulations of intelligence, but don't seek to create sentient thought in machines.Based solely on the descriptions of artificial intelligence that I've encountered in popular culture, it's never explicitly stated but always tacitly assumed that with sufficiently advanced technology, machines can be made to think.As this book discusses, this is not a universally acknowledged truth, but rather there is much disagreement among AI scientists as to whether this feat is even possible.

Some interesting history of AI research is covered, including the idea of Turing machines, and the robot "Shakey" who could perform simple tasks in a simplified environment, but ultimately failed to adapt when his surroundings became unfamiliar.Toward the end of the book, more recent developments are touched on, such as robot designs based on insects and robots who can negotiate more complex "real world" environments.

Overall a quick and interesting read like I've found most of the "Introducing..." books to be. ... Read more

Product Description
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general--all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:

• Collaborative filtering techniques that enable online retailers to recommend products or media
  
• Methods of clustering to detect groups of similar items in a large dataset
  
• Search engine features--crawlers, indexers, query engines, and the PageRank algorithm
  
• Optimization algorithms that search millions of possible solutions to a problem and choose the best one
  
• Bayesian filtering, used in spam filters for classifying documents based on word types and other features
  
• Using decision trees not only to make predictions, but to model the way decisions are made
  
• Predicting numerical values rather than classifications to build price models
  
• Support vector machines to match people in online dating sites
• Non-negative matrix factorization to find the independent features in adataset
  
• Evolving intelligence for problem solving--how a computer develops its skill by improving its own code the more it plays a game 

Customer Reviews (59)

Popular Web Algorithms Explained in Detail
He makes very good pointers sometimes I lose him through all the math. Don't buy this if you are not willing to pick up phython or if you don't have an extensive math background.All his examples are written in python. I wish he had a PHP version.

Excellent Resource, Clear and Concise
Excellent resource for beginners and experts alike. I was impressed with the organization and the concise explanations that nonetheless explained what you need to know to understand the methods in practical statistical programming being used today. The fact that all examples are given in working code ensures that everything you need to start programming your own applications is provided for you.

The only minor fault in my mind is that it could have been easier to explain some of the hairier concepts with mathematical formulas (which the author avoids, for legitimate reason) in an appendix. An appendix is provided with seemingly similar purpose, but is underdeveloped. This is a minor issue, as all concepts can be supplemented with a simple web search.

Great sample code in Python
A fun, fast read.Good depth, but still concise.The code is well written, broadly applicable, and easy to modify.This book is the opposite of A New Kind of Science.

Bold New Writing plus best O'reilly book ever
This book is spectacular, I love the way that the Author approaches a "new middle" ground of writing books.That is a book that is somewhere in between pure theory, and pure practice. That observation and follow through is simply genius.Python is an excellent choice for this as it can be easy to read.I had to study Python a little before I could totally digest the code.The book is around 300 pages but it is very dense, if someone else wrote it, it would be 600 pages.
Most O'reilly books are boring, useless documentation that you could find on the internet.This book is full of useful examples, showing you how to use "real" data, even how to get the "real" data. For that reason if you are not fond of O'reilly books, don't worry this one is different.

The downside: this book has over 1000 proposed errors and not 1 accepted errors on the O'reilly web site.Some of the code simply does not work as it's written in the book.You can download the code examples but even those do not work 100%.Check the O'reilly site to get the latest code updates.Also the book was published in 2007 and the internet has changed since then so the API's are a little out of date.By not updating this book they are doing the community and they author a huge disservice.

Intuitive and motivating book
I am not completely finished reading it but I already think it's a great introductory book which is strongly committed with transmitting intuition and comprehension of its material (machine learning) usually hard for regular people. It focuses mainly on implementation and application but some general coverage of the underlying theory is done to motivate inexpert readers. Examples are taken from the Web domain so this text can be very useful for people interested in combining BI and AI, among others. Personally, I approve using Python, which is not (yet) my favorite language, I consider it actually as a plus because it complements very well author's intention of simplicity which is all over behind the book design. This book seems to me like an excellent old school teacher among those ones who really take the right timing and words for carefully explaining you something probably difficult in an easy way so that you really will want to learn more about it. ... Read more

Product Description
Artificial Intelligence Illuminated presents an overview of the background and history of artificial intelligence, emphasizing its importance in today’s society and potential for the future. The book covers a range of AI techniques, algorithms, and methodologies, including game playing, intelligent agents, machine learning, genetic algorithms, and Artificial Life. Material is presented in a lively and accessible manner and the author focuses on explaining how AI techniques relate to and are derived from natural systems, such as the human brain and evolution, and explaining how the artificial equivalents are used in the real world. Each chapter includes student exercises and review questions, and a detailed glossary at the end of the book defines important terms and concepts highlighted throughout the text. ... Read more

Customer Reviews (7)

Great text on AI
My undergraduate AI class used this textbook. The writing was never dry and provided lots of information for someone new to the field of AI.

Not Feeling Very Illuminated
This was the textbook for a college AI course I took. I wouldn't recommend this book for an introduction to AI. Most topic discussions were cursory and required additional online research. There were very few examples to illustrate the subject material. Those that were provided were very confusing. I actually learned more from the internet searches I ended up doing than from this textbook. I was looking forward to this class, but this textbook did nothing to make my learning experience any better.

Excellent and outstanding service
Excellent and outstanding service.
Thank you for time and business.

V/R

INTULECT

Disappointing
A big fan of the COMPUTER SCIENCE ILLUMINATED text, I had high hopes for this as a good text for my undergrad class on A.I..I was sorely disappointed; this text is far too shallow for even a middle-level undergrad course. It also contains several errors, although that may be expected of a first edition.

Artificial Intelligence Illuminated
It's new one, which has a great quality. And very quick delivery. Perfect purchase to me. ... Read more

Product Description
In this mind-expanding book, scientific pioneer Marvin Minsky continues his groundbreaking research, offering a fascinating new model for how our minds work. He argues persuasively that emotions, intuitions, and feelings are not distinct things, but different ways of thinking.

By examining these different forms of mind activity, Minsky says, we can explain why our thought sometimes takes the form of carefully reasoned analysis and at other times turns to emotion. He shows how our minds progress from simple, instinctive kinds of thought to more complex forms, such as consciousness or self-awareness. And he argues that because we tend to see our thinking as fragmented, we fail to appreciate what powerful thinkers we really are. Indeed, says Minsky, if thinking can be understood as the step-by-step process that it is, then we can build machines -- artificial intelligences -- that not only can assist with our thinking by thinking as we do but have the potential to be as conscious as we are.

Eloquently written, The Emotion Machine is an intriguing look into a future where more powerful artificial intelligences await.

... Read more

Customer Reviews (24)

Good job
The book arrived in good condition. What I did not enjoy that much, was the black marker line on the side of the book, over the pages. Overall, it was a good deal and I would buy again.

A brilliant book about the mind.
The ''Emotion Machine'' by Marvin Minsky is an introduction to how our minds work.
An endeavor to understand mind (thinking, intellect) in terms of its design (how it is
built, how it works).
Sure, the inner workings of the mind sometimes appear to be impervious to any kind of
scientific approach. Routine stuff like making mental models of the world, design plans,pursue goals and feel desires aren't all that routine, when you think about it. And the way it all plays together - from simple, instinctive kinds of thought to more complex forms, such as consciousness or self awareness - is obviously very complex.

It would be very easy to get stuck in too much detail or to be too superficial. But somehow Minsky finds the right balance. So overall, the Emotion Machine is a brilliant introduction to how our minds work.

Often he will give us an idea about what must be going in computational terms, and then shield us from the usual deluge of ''neuro-technical'' terms. Because (in his own words) ''research on the (actual nitty gitty of the) brain is advancing so quickly that any conclusion one might make today could be outdated in just a few weeks.'' In one reviewers words: ''The Emotion Machine rewards careful reading. You'll learn a lot about how your mind works, even if you won't be all that much wiser about what is actually going on within your brain.'' :-)

Nevertheless, the book is obviously based on the latest advances in computer science, psychology,neuroscience, engineering etc. And certainly, his book is not a bad place to start if one wants to be a little wiser on what goes on inside our heads.
A wonderful book.

-Simon

Simple and brilliant framework for understanding mind.Is it strong AI done right at last?
Early efforts to model human-like thinking with machines using rules were interesting but failed in a number of ways to capture even simple ways that humans think. Marvin Minsky, AI pioneer at MIT, insists that we understand the mistakes and can begin to appreciate how the mind actually works in functional terms from the lessons we have learned. Learninig from our past mistakes, what a novel idea.

To put this into perspective, the question of whether a machine model can adequately describe a brain has long been considered in terms of either strong AI or weak AI. Most people find weak AI plausible: computers can solve certain kinds of problems better than humans. We mostly balk at strong AI however: machines can literally think like humans and solve the same kinds of problems just as well.

In The Emotion Machine, Marvin Minsky presents a very machine-like architecture that he claims actually represents the way real minds probably work in fundamental respects. That sounds pretty much like strong AI. So a lot of people will reject the concept of this book out of hand. I think that would be a mistake. Minsky has done a very good job identifying plausible specifics of why AI programs have failed to deliver on, where they have actually managed to deliver, and speculates on how we can fill in the gaps.

No, he doesn't spend time arguing against Searle's Chinese Room or other conundrums of AI, he just presents his case and gives examples in a clear, simple, accessible way. And I am persuaded that he probably gets a lot right. Probably more than he gets wrong. And that's a lot better than a lot of critics will give him credit for because it goes against both the mainstream disdain for strong AI and the mainstream love of flashy neuroscience images.

Minsky skips right on past the issue of connectionist networks vs. semantic networks and simply posits that we had to evolve semantic representations at some point. How is left as an exercise for neuroscientists. There is a lot of "details to be filled in later" sort of thinking here, so don't look to this book as a detailed physical model of the brain. This is a high level functional model of the mind and I like it.

So I claim that this is an important book that seems to promise a 21st century reboot of scientific naturalism as our guiding philosophy for the future. Minsky takes on nothing less than an overall architectural model for the mind in natural terms. It is brilliant. Too brilliant to be appreciated in its time because Minsky makes complex ideas so accessible that the biggest challenge for this book is that people will not appreciate its power. It reads like a simple AI model of a mind, but it is much deeper than that because of the amount of deep thought that has gone into it and the consideration of the weaknesses as well as strengths of previous AI programs.

We are currently in the grip of a widespread fascination with poorly understood pop neuroscience, and most readers will be deeply disappointed that this book does not attempt to wrestle with brain science at all. I think that's a strength because it means Minsky is not falling into the weird metaphysical spins that we too often see in pop neuroscience books, especially those by non-researchers and over-enthusiastic under-trained journalists.

What Minsky is doing here is simply coming up with a logical model of what a mind has to be able to do to provide the capabilities that we observe real human minds to possess. Sounds simple, right? No, not at all. The reason Minsky has accomplished something special here is that he recognizes many of the powerful fallacies we usually fall into when we introspect about thinking and rely on traditional models. We tend to think of emotions and reasoning as separate kinds of things, and then we talk about how they are both needed and how they interact. But as Minsky points out, both neuroscience and psychology seem to provide us evidence that these are points on a continuum, not different kinds of things. Minsky takes that seriously and builds on it.

The result is something amazing that looks like a simplistic mechanical model of the mind but captures some deep insights into how minds really work.

The central implication of Minsky's model is an epistemological stance that resourcefulness in human thinking is a matter of switching between different kinds of representations, each used in a different way of thinking, each of which captures something essential about specific things in our world while neccessarily leaving out other details. A mind can't comprehend everything at once. Some decisions simply don't have an optimal answer because they look different from different angles.

The key concept underlying Minsky's model is that minds as we think of them had to start with simple rules for recognizing and responding to cues, had to be able to incorporate goals in some form in those rules as well, and then eventually had to be able to recognize kinds of problem and activate appropriate ways of thinking. It makes sense to think of this in terms of logical levels of recognizers and responders, and importantly, what Minsky calls "critics" and "selectors," where each new level provides some way to resolve conflicts that arise in the level below it.

So conflicts in our instincts can be resolved by learned rules, conflicts in learned rules can be resolved by deliberation strategies, and in turn levels with different kinds of representations of the problem and eventually the problem solver and their own ways of thinking. Once the problem solver can represent themselves and their own thinking, we have the power to shape our own thinking in meaningful ways.

I'm really not doing justice to this book in this review, because it's power is in the details of his examples and how they illustrate the architecture at work. Suffice to say that I think if you find a functional architecture of the mind of interest, I highly recommend this book. I think it gives a much more fundamental understanding of how minds most probably work than any amount of flashy recent brain scans, and certainly more than untestable holistic and quantum mechanical theories will ever tell us until we better understand the functional design. Neuroscience in the future will, I believe, be filling in the details of a framework very much like this one.

brilliant explanation of the mind
Minsky gives us an accounting for how the mind might work that is consistent with the neurological/anatomical make up of the central nervous system.He "de-mystifies" thinking about thinking, and points us in a promising direction for the study of mind.The Psychology of Positive Thinking

Worth the read.
Minsky presents interesting new ideas on understanding ourselves. It makes sense that the mind, like the body, may seem simple on the outside but is amazingly complex on the inside. ... Read more

Product Description
The increasing trend of multimedia data use is likely to accelerate creating an urgent need of providing a clear means of capturing, storing, indexing, retrieving, analyzing, and summarizing data through image data.

Artificial Intelligence for Maximizing Content Based Image Retrieval discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field. Providing state-of-the-art research from leading international experts, this book offers a theoretical perspective and practical solutions for academicians, researchers, and industry practitioners. ... Read more

Product Description
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries. ... Read more

Customer Reviews (4)

History of a Remarkable Technology
This is an extremely literate, well written history of the first fifty years of AI by someone who fortuitously came in on the ground floor of this field.Nilsson's perspective is unique and invaluable for anyone interested in broadening their horizons, and in appreciating how many talented and driven individuals have contributed to AI's successes.

As a lay reader, I skipped the notes and many of the technical details and diagrams.I enjoyed the many interesting references scattered through the text. Just to give a flavor of these, in the first chapter alone there are references to Homer's "Iliad", Ovid's "Metamorphosis", The Talmud, opera (Offenbach's "Tales of Hoffman"), and theater, Capek's "R.U.R."I won't mention more of them here but leave them for you to discover, choice morsels all.Although this is a scholarly work, it's accessible to anyone who is interested in what AI is all about.
AI has already become an integral part of our lives.It's used for computing driving directions, interactive computer games, aircraft control, credit card fraud detection, vending machine currency recognition, robot control, speech recognition, and face identification, to name just some of the more prominent examples.

I came away marveling at how far this field has come in 50 years and convinced of the need for more basic research.Most of the important inventions were due to basic research.At the time, the results, to an untrained eye, looked stunningly simple.People thought, "What good is that?" We're now reaping the harvest of those years of early work, and one hopes that, along with applications, basic research in the field will continue.

This book is a significant contribution to the history of science.

recommended!
There is a great deal of good material here. I wonder if the general problem of producing a history of AI would not have been better decomposed into a set of mini-histories each concerned with a particular topic and occupying a single chapter. For example, NLP, machine vision, robotics, knowledge representation, vagaries of public/private financing, major commercial deployments, etc. each could have been addressed in a single chapter. In this book, individual topics pop up again and again in interleaved fashion as the author's single timeline unfolds. This may be a bit disconcerting for readers not already well versed in the field.Other advantages of a modular approach to the history of AI rather than a simple sequential approach are ease of updating the text for future editions and the ability of subject matter experts to quickly find and provide constructive feedback in their areas of expertise.

A minor irritation was the use of URLs in body text rather than confining them to end notes. Most authors would like their books to be timeless; the use of highly fragile URLs in body text seems to contradict this goal.

I suspect that this is the best history of AI we have so far. I recommend this book to anyone interested in the field.

An engaging, accessible and definitive history of artificial intelligence
Nils J. Nilsson's book begins with the story of how artificial intelligence originated in 1956 at a Dartmouth summer project that had the goal of "making a machine behave in ways that would be called intelligent if a human were so behaving." It relates how inthe fifty-plus years that followed, AI has been the subject of overly-optimistic predictions, academic arguments that its goals are unachievable, funding excesses, and funding droughts.But the underlying reality is that AI has contributed key components to the technology foundations that shaped the modern world, and indeed has transformed our view of machines and of our relation to them.

The algorithms that compute your driving directions, and also compute the paths of characters in video games? They rely on results from AI research on mobile, intelligent robots.Those surprisingly high-quality voice response systems we encounter when we phone a customer-service number?They use results from AI research in speech recognition. The recommender systems ("You might also like") used by many web vendors? They use machine learning methods whose history is described by Nilsson. And AI technology is embedded in a host of less-apparent applications ranging from medical devices to automated securities trading systems.

Nils J. Nilsson's comprehensive account of the evolution of AI covers the field from its inception to recent times.All the major sub-fields of AI receive attention--from game playing to automatic problem solving, from computer vision to speech and language understanding, from expert systems to machine learning and probabilistic reasoning--allthese and more are covered.

Nilsson enriches his account by viewing major developments through a multi-faceted prism. He describes AI's challenges, the approaches adopted and the landmark systems in just enough detail to give the reader real insight into the technical substance of the field.He also describes the funding issues and controversies that have swirled around AI since that very first Dartmouth meeting.And he introduces the reader to scores of brilliant, frequently colorful, characters whose contributions and opinions have influenced the course of developments.

For the AI practitioner, this book is a rare example of that often proclaimed, but seldom sighted species, the "essential volume" for your library.Your perspective on AI cannot help but be enhanced; you'll gain an increased appreciation for the time it takes for a good idea to mature and find a place in the world; and you may even be encouraged to revisit nearly-forgotten ideas that have relevance to current research issues.

But the book has appeal for the general reader as well.Nilsson is a masterful teacher and storyteller, and his description of timeless philosophical issues and intellectual challenges are as clear as you will find in as confined a space.Technical approaches are profusely illustrated and diagrammed, but remain accessible to any reader with an active curiosity.The tone of the book is straightforward and conversational, with neither the stuffiness of a self-important academic nor the breeziness of a science popularizer.

Predictions about AI have proven hazardous for 50 years, but I'll make one here:It will be a long time before any writer attempts a sequel to this unique and valuable volume.

Accessible to everyone- A lucid account of how AI has become a pervasive part of our lives
Professor Nilsson's humanistic account of the dreamy beginnings: Venus bringing an ivory statue of a beautiful maiden to life, "The girl felt the kisses he gave, blushed, and raising her bashful eyes to the light, saw both her lover and the sky"; and continuing on in an intuitive sequence from "early explorations" to "the quest toward human-level Artificial Intelligence" is a readily readable and engaging tour de force.

The scope is grand and encyclopedic; it is the culmination of a lifetime of brilliant scholarship and acclaimed teaching. ... Read more

Product Description
A revision of an established text for undergraduate and postgraduate Artificial Intelligence courses, this text incorporates the latest research and methods. Special features include: a broad survey of AI methods; real-world examples and detailed algorithm descriptions, which are not language specific and which help students grasp the practical applications of AI theory; and a chapter on basic problem solving methods which shows students the major structures in which artificial intelligence programs can be built.Amazon.com Review
Artificial Intelligence is a somewhat datedintroduction to the subject. If you are looking for an introduction tocore topics in artificial intelligence (AI), such as logic, knowledgerepresentation, and search, this book has something to offer. However,if you want to learn about some of the newer areas of AI, such asgenetic algorithms, neural networks, and intelligent agents, you willwish to select a different text. ... Read more

Customer Reviews (5)

A really bad textbook.
This is one of the worst books I have actually seen on the subject of Artificial Intelligence. This book is aimed at both advanced undergraduate and graduate studies in AI. It does cover a large number of topics as expected by an introductory book on AI.

The main problem with this book is its use of language. The book tries to explain everything in formal english. This makes the explanations extremely hard to understand without rereading it a number of times. There is no time spent in giving explanations in simpler prose or resorting to mathematical formalism wherever needed. But instead the book reads like Principia Mathematica, except that the words used are familiar English words instead of Greek symbols.

Of course, a seasoned veteran of the subject can easily make sense of most of the things in the book. But the book is designed to throw off any new student of the subject. Unfortunately the book does not even work as a handy reference for a veteran. Finding stuff in the book does require a lot of reading through difficult prose.

Overall this is a bad book, both has an introductory text book and as a reference book. If you are looking for an AI textbook: I would highly recommend Artificial Intelligence: A Modern Approach by Russel & Norvig.

Very Crisp
It requires a number of readings to understand. No detailed examples or code for most of the topics. Not clearly explained the relation between Memory-based reasoning and case-based reasoning. If you are already havesome knowledge in AI or if you want to know in some detail of varioustopics of AI then this is a good book. Probably Nils J Nilson's AI book maybe a good one to start and then use this book.

Good basic introduction, but little else.
I am a games programmer who was wanting to get better understanding of some artificial intelligence applications and theory. This book provided a reasonable introduction, but very little more than I had picked up from myown experience. Search algorithms, State spaces, goal oriented planning andall the basics are covered, but it doesn't go much farther from there. Ifyou know NOTHING about AI it could be a useful addition to your library,but if you're even a novice like myself with introductory understanding itprobably won't offer you anything new.

A MUST BE for the AI interested.
This book is one of the best books I've seen in AI field. Our instructor recommended this book, and I found that he was right in his opinion. This is a MUST BE textbook for every teachers (students) who want to teach(learn) AI to be a good one in AI field

Great Introduction
This is the best introduction about AI I know. It is well readable but still gives precise information. I recommed this as yout first book on AI (second one could be e. g. Winstons AI-Book). ... Read more

Product Description
Reveals how the project originated and how it was brought to fruition through the efforts of two great movie directors.Film is the medium of the modern age, and in this spectacular, large-format publication, one of the pinnacles of contemporary moviemaking is celebrated. A.I. Artificial Intelligence (2001) was a collaboration between two cinematic giants: Stanley Kubrick and Steven Spielberg. Here, the directors’ combined visions and sensibilities are presented along with the work of their remarkably talented colleagues—above all, Chris Baker, the film’s conceptual artist.

At the heart of the book are Baker’s drawings, many never before seen. Commissioned by Kubrick and used in Spielberg’s eventual production designs, the drawings display Baker’s imagination and rare technical skill. Accompanying the drawings are extracts from Kubrick’s notebooks, stills from the finished film, and photographs of behind-the-scenes action, highlighting the use of pioneering special effects, animatronic work, and the “virtual studio.” 300 color, 100 b&w illustrations ... Read more

Customer Reviews (4)

A.I. Artificial Intelligence: From Stanley Kubrick.
A.I. Artificial Intelligence: From Stanley Kubrick.
Wonderful colored pictures and great information on the feature film.
One draw back not enough behind the scenes on the miniatures from ILM.

Very nice book overall!

Great and amzing book............but
Why not include the DVD of the movie or some special features as a Tie in to aid the cause

Finally...
A great and beautifully produced book about an enigmatic and mysterious film. The large format reproductions of Chris Baker's artwork are gorgeous. Stanley Kubrick's notes, annotations from Brian Aldiss, Ian Watson and Spielberg are gold. The editorials by Jan Harlan and Jane Struthers are fascinating and insightful, and at times quite moving -- especially Mr. Harlan's comment in the introduction, remarking on Stanley Kubrick's philosophy of filmmaking: 'First love it, and then worry about how to do it.'

For full disclosure, "A.I." was somewhat of a personal obsession, which haunted me from first reports that began appearing in the early days of the Internet rumor mill. Around the time of the film's release, I had the privilege to interview many of the filmmakers for an article about the film for Cinefex magazine, which I'm honored to see included in the 'recommended reading' notes of this book. One thing that my article lacked was Stanley Kubrick's voice. This book gives you that, in the annotations accompanying Chris's artwork and the observations of his colleagues. Bravo to Chris and to Thames & Hudson for pulling this material together; and to Messrs. Harlan and Spielberg, thank you for allowing this book to happen. It's long overdue, and it is a treasure.

Highly recommended.

Joe Fordham
Cinefex, associate editor

Very well researched and in depth
Watch Video Here: http://www.amazon.com/review/R3DZKVVD4Q7UAQ I was a bit surprised when I saw this book, published eight years after A.I. Artificial Intelligence was released. Time seems to stretch out with everything with this movie.

This book looks in depth at the production and also analyses the whole film thoroughly. If you don't already know, the film is inspired by a short story called "Super-Toys Last All Summer Long" written by Brian Aldiss in 1969. In 1976, Stanley Kubrick approached Brian Aldiss, and later with Steven Spielberg in 1984. With authorization from Kubrick before he passed away in 1999, Spielberg manages to finish the film in 2001. What happens during within all those time is all in the book. It's incredibly well researched and put together.

Besides production, there's also an extensive analysis of the film, act by act, with interviews from staff. It explores the philosophy, science and social-biology issues with robotics in the future. There's even an essay written by the director from the Personal Robots Group from MIT Media Lab.

This is one huge book measuring almost 20 inches diagonal, if go you by tv/monitor sizes. The pages are so big that the short story from Brian Aldiss are scanned and reproduced with handwritten notes.

Also included are storyboards and concept sketches from Chris Baker, as well as many photos from the set. It's interesting to see how the concept art evolved into actual sets and the discarded ideas. I didn't know that Rouge City, the one with lots of bright lights, is actually a miniature set. And Teddy, the bear, has more articulation joints than T-Rex from Jurassic Park. There are also extracts from Kubrick's notebooks but his handwriting is difficult to read.

This is a nice super-sized book looking at the art and making of the film. Recommended for fans of the movie.

(More pictures are available on my blog. Just visit my Amazon profile for the link.) ... Read more

Product Description
The third edition of this guide to Prolog and Artificial Intelligence has been updated to include key developments in the field. Divided into two parts, the first part of the book introduces the programming language Prolog, while the second part teaches Artificial Intelligence using Prolog as a tool for the implementation of AI techniques. ... Read more

Customer Reviews (9)

especially good for A.I.
A new edition will be out soon, in 2010.This is an excellent book on Prolog *and* on AI.

For example, chapter 19 is an introduction to inductive learning in first-order logic, an advanced topic rarely found in introductory books.The example program HYPER is a very powerful learner as compared to other "propositional" machine learning methods such as decision trees, neural networks, or support vector machines.I have ported HYPER to Lisp and am still exploring it.

Prolog is not a very popular language nowadays, but basic knowledge of it is still essential to learning logic-based AI.

Why is this the the best textbook on prolog?
Although this text is always mentioned in the same breath as other introductory textbooks on prolog, I don't think I've ever seen it described as "the best."
The book which usually takes the palm in such comparisons is"Art of Prolog."While "Art of Prolog" is an outstanding book, I think that now, in 2006, it has been eclipsed by the 3rd edition Bratko's book.Why?

Simply this: Bratko's textbook is (as far as I'm aware) the _only_ textbook on prolog which treats the language as a living, developing language!Other textbooks are great for their time, but they are unfortunately stuck in their time.Its as if nothing has happend to the prolog language since February 16, 1987.But this isn't true at all!

The biggest case in point: constraint logic programming!Bratko's text is the only introductory prolog textbook to even acknowledge the existance of CLP.And Bratko gives very lucid descriptions of it, along with very helpful examples and challenging exercises.

Another case in point: inductive logic programming!An entire new branch of machine learning theory has risen, based on logic programming, and NONE of the other introductory prolog textbooks cover it?Come on guys!

I would love to see a 4th edition of this book, because since this one has been published, logic programming has moved even further ahead.Constraint handling rules (CHR), logical functional languages (like Curry), using prolog for the semantic web, etc etc etc.It might be the best kept secret in computer science, but logic programming is really still one of the most exciting areas of programming, and Bratko's book does the best job of staying abreast of, and conveying the excitment of, this living and dynamic field.

Great book for learning AI with Prolog, but....
... a horrible Prolog tutorial.

This is not a good first book on Prolog. If you are new to Prolog and Logic Programming, you should read 'Art of Prolog' first.

Prolog is quite different from other languages, and you'll need some time to get it. This book doesn't give you that time: after briefly introducing the basic concepts, Bratko dives at breakneck speed into recursion and list processing.

Don't get me wrong, this is a magnificent book on how to do AI with Prolog, but it shouldn't be your first Prolog book. It's an excellent second book.

An excellent introduction to Prolog and concepts in AI
Professor Bratko has done a tremendous job of putting all the fundamental concepts of Prolog and its applications in various areas of AI. Although this book is focused on Prolog, the concepts that he has discussed are so fundamental that they can be implemented in other languages like Java as well.

I recommend this book to everyone who wants to learn Prolog. I would also recommend the readers to use a Prolog system to work out the examples and exercises as s/he goes through every chapter. A DEC10 Prolog system (like SICStus Prolog) would probably be the best companion for this book.

I thought the book could be better
I find the book does not adequetly explain the more complex code examples.First of all the code is not adequetly commented.Secondly, it does not explain the code well for programmers.First when introducing a program like in the expert systems shell chapter it should first define an interface for the program, and explain each goal listed.It should adequetly explain what each goal and clause should hope to achieve.Also, for the more complicated programs it should draw some type of diagram, maybe a flow chart or something that explains the concepts involved.It leaves too much figuring out and guessing for the reader.It is not very user-friendly!
On the positive side, it does an adequate job of explaining concepts when complex code is not involved.I found that I could follow along on even the more advanced chapters mostly everything at least until code was suddenly introduced.Then it became a guessing game as to what it was trying to do.
The author does not seem to realize that it is more difficult to try to understand somebody else's program than it is to write your own program from scratch.As a consequence the reader wastes a lot of time trying to guess what his program is doing.
Note: this review is of the 2nd edition and does not necessarily reflect the 3rd.But, then again, every other review on this page prior to mine is about the 2nd edition as well! ... Read more