| ||||||||||||||||||
 Trade In this Item for up to £22.45
Trade in Artificial Intelligence: International Version: A Modern Approach for an Amazon.co.uk gift card of up to £22.45, which you can then spend on millions of items across the site. Plus, get an extra £5 when you trade in books worth £10 or more until June 30, 2012. Trade-in values may vary (terms apply). Find more products eligible for trade-in.
|
Frequently Bought Together
Product details
|
More About the Author
Product Description
Product Description
Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence.
Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence.
According to an article in The New York Times, the course on artificial intelligence is “one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world.” One of the other two courses, an introduction to database software, is being taught by Pearson authorDr. Jennifer Widom.
Artificial Intelligence: A Modern Approach, 3e is available to purchase as an eText for your Kindle™, NOOK™, and the iPhone®/iPad®.
To learn more about the course on artificial intelligence, visit http://www.ai-class.com. To read the full New York Timesarticle, click here.
About the Author
Stuart Russell was born in 1962 in Portsmouth, England. He received his B.A. with first-class honours in physics from Oxford University in 1982, and his Ph.D. in computer science from Stanford in 1986. He then joined the faculty of the University of California at Berkeley, where he is a professor of computer science, director of the Center for Intelligent Systems, and holder of the Smith–Zadeh Chair in Engineering. In 1990, he received the Presidential Young Investigator Award of the National Science Foundation, and in 1995 he was cowinner of the Computers and Thought Award. He was a 1996 Miller Professor of the University of California and was appointed to a Chancellor’s Professorship in 2000. In 1998, he gave the Forsythe Memorial Lectures at Stanford University. He is a Fellow and former Executive Council member of the American Association for Artificial Intelligence. He has published over 100 papers on a wide range of topics in artificial intelligence. His other books include The Use of Knowledge in Analogy and Induction and (with Eric Wefald) Do the Right Thing: Studies in Limited Rationality.
Peter Norvig is currently Director of Research at Google, Inc., and was the director responsible for the core Web search algorithms from 2002 to 2005. He is a Fellow of the American Association for Artificial Intelligence and the Association for Computing Machinery. Previously, he was head of the Computational Sciences Division at NASA Ames Research Center, where he oversaw NASA’s research and development in artificial intelligence and robotics, and chief scientist at Junglee, where he helped develop one of the first Internet information extraction services. He received a B.S. in applied mathematics from Brown University and a Ph.D. in computer science from the University of California at Berkeley. He received the Distinguished Alumni and Engineering Innovation awards from Berkeley and the Exceptional Achievement Medal from NASA. He has been a professor at the University of Southern California and a research faculty member at Berkeley. His other books are Paradigms of AI Programming: Case Studies in Common Lisp and Verbmobil: A Translation System for Faceto-Face Dialog and Intelligent Help Systems for UNIX.
Tags Customers Associate with This Product(What's this?)Click on a tag to find related items, discussions, and people.
|
Sell a Digital Version of This Book in the Kindle Store
What Other Items Do Customers Buy After Viewing This Item?
Customer Reviews
The mathematics is understandable, I didn't find pages with more formulas than text as I saw in other books in the field. So it's not a scary sight.
I think that compared to any other book on AI this is way beyond, and it is the one to buy as it saves a lot of time of searching the web for answers. So if you need a book on AI, if this book cannot help you, no other book will. And another aspect I really appreciate at this book is its price. I can't believe when I read it that it was the cheapest among my latest acquisitions on ai and machine learning, and it contains so much more useful information than any of them! This is a great thing. You will notice that the paper quality is not as high as in other books, but this is something I love. I don't want to pay for the glossy paper, as I'd rather pay for more pages!
Just another point for who might be interested in case based reasoning : this book almost doesn't mention it! It's only mentioned in a Bibliographical and Historical chapter, in one paragraph. Therefore, I'd advise to check the table of contents and see if the authors write about what you're interested in. If they do, that'll be a pleasure to read!
It has many algorithms from the most diverse areas, but the pseudo-code implementations are weak and way too general to be of any use, further more, their evaluation function is also not recommendable in most cases.
Other than that, it is a fluid book with hundreds of illustrations and schemes that will help any reader understand how things should work easily in most cases.
It is up to date and gives a lot of information about new approaches to AI and machine learning that have been developed in the last 10 years.
However it is not a light read. There is an assumption that you are already familiar with the mathematics around probabilities, linear algegra and matrix manipulation, as well as being able to recognise a wealth of greek symbols used in the sometimes confusing notations used. There are a few pages about these mathematical topics in an appendix bit you will probably need to brush up with other material referenced outside of the book if you want to fully understand or try to apply the probabalistic learning techniques described.
If you just want to know what AI is about then there are a lot of easier introductory books around, but if you want to know in detail the sort of probabalistic learning techniques that allowed the Stanford University team to win the $2million prize for the DARPA autonomous vehicle challenge then this book is one of the few around that covers the material in depth.
Very good book and excellent delivery!
Listmania!
Look for similar items by category
Look for similar items by subject
Feedback
- Would you like to update product info or give feedback on images?
- I am the Author, and I want to comment on my book.
- I am the Publisher, and I want to comment on this book.
|
