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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 for intelligent systems 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

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Artificial Intelligence A Modern Approach

Ses 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 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 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 interested in the idea of developing stupid machines that function 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

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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 agentdistributed AI and game theory; probabilistic approaches to learning including EM; detailed descriptions of probabilistic inference algorithms NEW Updated and expanded exerci Holy balls this book has a lot of pages I also don t know why these things always have to have separate international editionsIt 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 TranslateThere s a few 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 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 textbookIn 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


10 thoughts on “Artificial Intelligence A Modern Approach

  1. says:

    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 vol

  2. says:

    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 i

  3. says:

    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

  4. says:

    Holy balls this book has a lot of pages I also don't know why these things always have to have separate ``international'' editionsIt starts off strongly for a few hundred pages but then for no reason at all devotes

  5. says:

    5 stars because there is uite simply no substituteArtificial 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

  6. says:

    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 but it's very popular for AI classes so any good college library should have a copy

  7. says:

    The Bible on computational decision making I use this term as this book is not just about the AImachine learning we consistently hea

  8. says:

    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 ther

  9. says:

    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 forgotAIMA doesn't presume a ton of background be

  10. says:

    It was written like a text book for undergrads with extensive coverage of many topics However I was looking for 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