S well as scruffies and neats "Key figures events and schools of thought span multiple institutions on multiple continents In short a " figures events and schools of thought span multiple institutions on multiple continents In short a challenge facing anyone wishing to survey Artificial Intelligence is simply coming up with a unifying themeThe 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 indispensableWith 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 uality 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 acuired by So to some extent Peter Norvig powers both Google and So one can probably claim not without ustification that AIMA emphasizes Bayesian probability over other approachesFinally 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 seenSo 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 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 ob of keeping the contents up to date with the latest happenings in AI while keeping the readers sane Overall
Thumbs Up This Monumental Work up This monumental work 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 CVsWhat was that Ah yes as a matter of fact it does cite one of my papers How did you gues. 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.
CHARACTERS ✓ MY-KASPERSKY.CO.UK ↠ Stuart RussellIt 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 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 ust to see 1 is there such a thing as AI or are we ust 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 udgments 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 ust 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 For
A TEXTBOOK THIS IS AMAZINGLY ACCESSIBLEtextbook this is amazingly accessible 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 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 hundredlevel probability and statistics before devolving into essentially pointless mathematical show boating for another few hundred 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 ustify 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. 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. 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 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 " science We used this book for CS4600 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 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 beyond some programming experience exposure to mathematical notation and a basic understanding of computational complexityalgorithmic efficiencyThe 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 betweenDespite that there is no 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 The Bible on computational decision making I use this term as this book is
not ust about the AImachine learning we consistently hear about it s much This textbook tends to perfection withjust about the AImachine learning we consistently hear about it s much This textbook tends to perfection with stone left unturned Looking forward to the next edition which at the accelerating rate of innovation looks overdue the following sentence surely
feels outdated Current Go programs play at the master level on a reduced 9 9 board but areoutdated Current Go programs play at the master level on a reduced 9 9 board but are at advanced amateur level on a full board There are 2 aspects I particularly enjoyed 1 the historical sections at the end of each chapter the introduction also gave a fascinating history of AI and its relationship to other fields neurology logics cybernetics 2 I also liked all the gaming aspects such as the Wumpus World which I didn t know before I truly wish I had discovered that book when it was first published in 1995 sigh 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 will recall terms like symbolic vs connectionist vs probabilistic 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.