Read Artificial Intelligence: A Modern Approach by Peter Norvig Stuart Russell Online


For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application forFor one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa...

Title : Artificial Intelligence: A Modern Approach
Author :
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ISBN : 9780137903955
Format Type : Hardcover
Number of Pages : 1132 Pages
Status : Available For Download
Last checked : 21 Minutes ago!

Artificial Intelligence: A Modern Approach Reviews

  • Manny
    2019-02-25 06:41

    This monumental work, which completely dominates the AI textbook market, has been compared with classics like Watson's Molecular Biology of the Cell, and eminently succeeds in its goal of providing a clear, single-volume summary of the whole field of Artificial Intelligence. As pointed out on the book's home page, it is used in over 1200 universities in over 100 countries, and is the 25th most cited publication on Citeseer and the 2nd most cited publication of this century. The occasional suggestion you may hear that it "has passed its sell-by" or "gives a decent picture of Good Old-Fashioned AI" can unhesitatingly be written off as envious carping from academics who wish they'd got something even a tenth as impressive on their CVs.What was that? Ah, yes, as a matter of fact it does cite one of my papers. How did you guess?

  • Nick Black
    2019-02-23 04:32

    Heh, I opened this up to find the ISBN and found dried blood all over the pages, suggesting I read this during my cocaine-intensive period back in 1999-2000. That's fitting, since cocaine and the study of artificial intelligence seem to enjoy several similarities -- incredible expense as a barrier to entry, exciting short-term effects (see: euphoria, A* search) but letdowns upon prolonged use (see: addiction, combinatorial explosions), and they've both ruined plenty of fine careers in computer science. We used this book for CS4600, but I only got halfway though that semester and remember little of it (see: careers in computer science, aforementioned negative effects of cocaine on). I went back and read most of this in 2003, and found solid coverage of most everything useful I'm aware of from AI.

  • Wooi Hen Yap
    2019-02-27 06:57

    Wants a book that explains broad and deep AI yet in laymen term (nearly)? This is IT. Of all the AI books I have read, this one is arguably the most accessible to undergrads (CS, EE background) It assumes only minimal mathematical formalities and pretty much the maths things are self-contained. The authors did a great job of keeping the contents up-to-date with the latest happenings in AI, while keeping the readers sane. Overall, thumbs up!

  • Koen Crolla
    2019-03-26 08:44

    Holy balls this book has a lot of pages. I also don't know why these things always have to have separate ``international'' editions.It starts off strongly for a few hundred pages, but then for no reason at all devotes several chapters to high school-level probability and statistics, before devolving into essentially pointless mathematical show-boating for another few hundred pages. Then it finishes off with an interesting but not really relevant and highly unrigorous (not to mention typo-ridden) overview of Google's various products (mostly PageRank and Google Translate).There's a few more chapters after that, but I think it's best to pretend they don't exist. Chapter 26 (Philosophical Foundations), in particular, was a fucking embarrassment, giving more unnecessary to idiots like John Searle and Ray Kurzweil, and wasting paper on absurd hand-wringing over off-the-wall science-fiction scenarios. AI is too legitimate and interesting a field to justify that sort of crap in a university textbook.In spite of all that, though, it's still a very good book, and a good overview of the field. I particularly liked that each chapter had an extensive section with historical and biographical notes at the end. If nothing else, it at least demonstrates that if the AI winter was ever a real thing (at least in terms of research activity and progress), it's far behind us now.

  • Paul
    2019-03-26 06:46

    5 stars because there is, quite simply, no substitute.Artificial Intelligence is, in the context of the infant science of computing, a very old and very broad subdiscipline, the "Turing test" having arisen, not only at the same time, but from the same person as many of the foundations of computing itself. Those of us students of a certain age will recall terms like "symbolic" vs. "connectionist" vs. "probabilistic," as well as "scruffies" and "neats." Key figures, events, and schools of thought span multiple institutions on multiple continents. In short, a major challenge facing anyone wishing to survey Artificial Intelligence is simply coming up with a unifying theme.The major accomplishment, in my opinion, of AIMA, then, is that: Russell and Norvig take the hodge-podge of AI research, manage to fit it sensibly into a narrative structure centered on the notion of different kinds of "agents" (not to be confused with that portion of AI research that explicitly refers to its constructs as "agents!") and, having dug the pond and filled it with water, skip a stone across the surface. It's up to the reader whether to follow the arcs of the stone from major subject to major subject, foregoing depth, or whether to pick a particular contact point and concentrate on the eddies propagating from it. For the latter purpose, the extensive bibliography is indispensable.With all of this said, I have to acknowledge that Russell and Norvig are not entirely impartial AI practitioners. Norvig, in particular, is well-known by now as a staunch Bayesian probabilist who, as Director of Search Quality or Machine Learning or whatever Google has decided to call it today, has made Google the Bayesian powerhouse that it is. (Less known is Norvig's previous stint at high-tech startup Junglee, which was acquired by Amazon. So to some extent Peter Norvig powers both Google and Amazon.) So one can probably claim, not without justification, that AIMA emphasizes Bayesian probability over other approaches.Finally, as good as AIMA is, it is still a survey. Even with respect to Bayesian probability, the treatment is introductory, as I discovered with some shock upon reading Probability Theory: The Logic of Science. That's OK, though: it's the best introduction I've ever seen.So read it once for the survey, keep it on your shelf for the bibliography, and refer back to it whenever you find yourself thinking "hey, didn't I read about that somewhere before?"

  • Carl
    2019-03-18 01:49

    For a textbook, this is amazingly accessible and interesting. if you have any interest in the topic, this is the book to read. It's $100 or more, but it's very popular for AI classes, so any good college library should have a copy.

  • Mohammed
    2019-03-24 05:32

    يعتبر هذا الكتاب أهم مرجع للدارس في مجال الذكاء الاصطناعي. الكتاب يعتبر مقدمة لمواضيع كبيرة جدا و متشعبة، فعيتبر بداية التخصص في الذكاء الاصطناعي. يتناول الكتاب مواضيع في تعلم الآلة وخوارزميات البحث وحل المشكلات. بعض أجزاء الكتاب تعبر من المراجع النادرة وخصوصا في فيما يتعلق بموضع الـ reinforcement learning.مؤلفي الكتاب بيتر نورفق و روسيل من الرواد في مجال الذكاء الاصطناعي.

  • Arjun
    2019-03-16 00:29

    A fantastic textbook that's not only a great introduction to AI but also serves as a survey course in technical writing. I only read about 75% of it but definitely plan on revisiting it. Re-reading some earlier chapters taught me how much I missed on a first read (or forgot).AIMA doesn't presume a ton of background beyond some programming experience, exposure to mathematical notation, and a basic understanding of computational complexity/algorithmic efficiency.The first 10 chapters or so are the best and the second half of the book can be a bit of a trudge as it devolves into mathematical masturbation. A lot of the chapters are better served by other resources – I highly recommend the CS188 lectures from UC Berkeley for supplementation. Unfortunately, some chapters are straight up bad (the chapter on Philosophical Foundations comes to mind), but these tend to be few and far between.Despite that, there is no more comprehensive book on AI. Read this, re-read this, and treat it with care – you will reap the rewards for a long time to come.

  • Luis
    2019-03-09 03:53

    A bit boring. Lacks good solved exercises. Very short on detail in some areas such as Neural Networks. Very "theoretical".However it does provide a good theoretical introduction to many subjects. I liked the chapters on search.

  • Nakosy
    2019-03-08 07:40

    It was written more like a text book for undergrads with extensive coverage of many topics. However, I was looking for more in-depth information on knowledge representation. But, it was too superficial for my need. May be, in 3rd edition it encompassed the latest ideas in this area.

  • Erik
    2019-03-17 03:44

    OK so I did not read this cover to cover, but I did look closely at much of what you might call the foundational chapters, just to see 1. is there such a thing as AI, or are we just hoping there will be and 2. what can I learn as a philosopher from AI, whether it exists or not. Goal 2 was much more important as I teach a logic of induction class and of course one major pillar of AI would be developing machines that can perform judgments under uncertainty and apply rational heuristics as well as humans do (which is not very well at all by the way). I found out that I already knew most of this, from studies of Bayesian reasoning (which is very tricky by the way and should not be blindly implemented like this without a clear view of the limitations), and the study of acyclic causal graphs (which is standard academy reading for philosophers). These graphs also admit of howlers and counterexamples as anyone knows. I am more interested in the idea of developing "stupid machines" that function more like neural networks and less like probability maximizers. The human brain is fundamentally (in my view anyway) a stupid-machine, full of crazy workarounds and faulty logic. The correct solution or path is virtually never the one evolution comes up with, it just grinds it out with massive armies of neurons and interconnections and lots of trial and error, but nothing one would call a computation, as in Turing machines. Elegant algorithms for computer vision have, I believe, nothing to do with the way the brain constructs the visual image. One philosopher's take.

  • Drew
    2019-03-04 05:52

    A comprehensive course in modern AI topics. While the book is dense with information, the authors provide clear explanations that will be easily picked up by the careful reader. An excellent companion to an undergraduate course in artificial intelligence.

  • Hasnaa
    2019-03-11 03:39

    من المراجع النادرة في الكلية اللي لقيت عقلي قادر على استيعاب كلامها :Dأسلوب بسيط وممتع كمان، للي مهتم بالمجال أو مش مهتم بس مضطر يقرأ فيهفي الحالتين لطيفالمشكلة الوحيدة طوله الرهيب، أتمنى ألحق أخلص أكبر قدر ممكن قبل الامتحان

  • James Ravenscroft
    2019-02-25 02:46

    This is THE book to read on anything to do with modern artificial intelligence. I regard this as my personal bible and would recommend it to anyone who is involved in technical artificial intelligence.

  • Jaslyn
    2019-03-22 02:37

    not bad for an intro: simple math, minimal jargon and pretty organized

  • Shahriar Hossain
    2019-03-07 04:38

    We call ourself Homo sepiens - man the wise .....

  • Daniel Korzekwa
    2019-03-16 04:35

    This is the most complete and comprehensive book I read on a subject of Artificial Intelligence so far and it's very well written as well. If you plan diving into AI really seriously and you are keen to invest some good amount of time going through 1000 pages of this book then I really recommend it for you. Great addition to this book is A.I. course led by coauthor of this book, Peter Norvig and Sebastian Thrun, a Professor of Computer Science and Electrical Engineering at Stanford University. Last three months I spent every day with both this book and A.I. course and it was the most fascinating learning experience I've ever head.

  • David
    2019-02-25 06:37

    It's a pricey book. It was used in my university on AI. It covers many AI topics including intelligent agents, searching, knowledge representation, machine learning, etc. There are enough examples, but not enough good and clear examples. The book is heavily biased towards First Order Logic as the way to do knowledge representation, making it good on Bayesian networks. Other topics like neural networks and machine vision would be better off read elsewhere. Overall, the book is not for light reading - you need to really concentrate on what you're reading to understand it.

  • Jean-marc
    2019-03-15 00:45

    Fantastic and comprehensive book on the different aspects of artificial intelligence (AI). I am attending Stamford cs221 online class (fall 2011) and I am also a member of the team translating the videos from English to French. Peter Norvig is a great teacher. The book and the videos complement each another very well. Even if you are not taking the course, or after you have took it, this book is a superb reference on the subject for graduate students and professionals alike. I highly recommend it to anyone interested in the field. #aiclass

  • Patrick Jennings
    2019-03-19 01:49

    Pretty much THE book to have on comprehensive artificial intelligence. AI: A Modern Approach is used in schools and universities across the globe. Don't expect implementations in anything but general pseudocode in this book. Although, you may check the repository at

  • Carl-Erik Kopseng
    2019-03-05 04:33

    One of the best technical books I have read, albeit on a hard topic. It's quite readable and a lot better than my AI lectures ever were. Must admit to only reading the first 12 chapters though. Its main weakness lies in the lacking coverage of "new AI" topics, such as evolutionary algorithms.

  • Franta
    2019-02-27 05:55

    What a nice and useful book!All the main AI (before 2000 or so) is here and the accompanying code in lisp and python is a good way to learn about the implementation details.I will surely remember this book when I am writing a similar one!

  • Jamison Dance
    2019-03-09 03:52

    The classic introduction to the field. Peter Norvig and Stuart Russell are great writers, and do a good job of explaining the concepts. Sometimes their bias shows, but that is something I am willing to put up with for a book that covers the field so well.

  • Mahmoud Adly
    2019-03-08 05:40

    That paradox of loving AI and hating the journey the center of math. Any ways, it is a reference after all. At least I know where to go when I have a problem.

  • ali
    2019-03-09 06:54

    abut artificial intelligence

  • Amirhosein
    2019-03-25 02:52

    Absolutely a must read for every A.I enthusiastic.The book covers most introductory topics in A.I and has challenging problems that you can use to make sure you understood the presented topic.

  • Kevin Clark
    2019-03-20 00:56

    Is mostly the history of AI, does little to teach you how to design AI...although I was never able to finish the book.

  • Tasnim DewanOrin
    2019-02-24 01:31

    This is holy grail i.e basic book for any AI researchers. I love the examples and everything it taught me while learning basic of AI.

  • Vishnu S Kumar
    2019-03-20 04:39

    Good for newbies.

  • Dimitar
    2019-03-13 08:55

    must read on AI