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AI Application Programming (Charles River Media Programming) Paperback – March 27, 2003
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Top Customer Reviews
All in all a very good book, and also a great Graduate level reference for the inner workings of actual Artificial Intelligence algorithms.
If you are well prepared, this book is to the point, and well worth the read. Prepare for a visit to College-level Physics theorems, as many algorithms given require a working knowledge of the advanced principles of the science.
Hope this helps-
This book is the second edition of the successful book by Tim Jones on different facets of AI, how they can be used, and how to write programs that implement the necessary algorithms. The book begins with a short but insightful chapter on the history of AI, followed by a series of chapters, each covering a specific AI technique. The last chapter covers the state of AI today. Each chapter begins with a short description of the technique covered, sometimes including parallels to the real world that are behind the algorithmic choices of the technique. Next, the algorithm is described, and a sample implementation is given and discussed. Last, the author presents examples of problems that can be solved by the given technique. This book basically replaces the first edition, as everything in that book is in this one plus the A* pathfinding algorithm, particle swarm optimization, classifier systems, reinforcement learning, and natural language processing. For several of the techniques variations and tuning opportunities are presented, allowing the reader/programmer to easily adapt the technique to a different problem of a similar type. There are also plenty of illustrations and diagrams, making the material easier to absorb. I highly recommend that you purchase this second edition, even if you already have the first edition. It is a worthwhile upgrade.Read more ›
However, there are two things I have to point out: One, the editing/basic correctness check of this book is kinda terrible. For example, P72 on Particle Swarm Optimization, the 4.2 formula is obviously WRONG and not consistent with the rest of discussion. Also on P74, the position vector calculation is wrong as well: it also seems the author/editor cut & copy two blocks of text.
Second, I don't like is the lack of explaination on certain important notations and equations, which is very important to be at least "self-contained" for such a "cover everything" book. For example, P210 on reinforcement learning, Equation 9.2 has a general explaination of what it is, but non of those notation/symbols in the equation make sense in the context.
So, in general, be aware its pro and cons.
The author explains and describes a number of algorithms and approaches to AI including classical path finding algorithms such as depth first search, breadth first search the A-star algorithm, as well as simulated annealing, the PSO algorithms (Particle Swarm Optimization), Adaptive Resonance Theory, what he calls classifier systems, and Ant Algorithms. He introduces Neural Networks focusing on feed-forward multilayer networks using back propagation learning. He also presents reinforcement learning and simple genetic algorithms. He discusses Artificial Life and Rules-based Systems and introduces fuzzy logic. There is a chapter on Natural Language Processing and another on Markov chains with the focus on the bigram model. Towards the end of the book there is a chapter on agent based systems applied to a web application.Read more ›
Most Recent Customer Reviews
One of the best book on Artificial Intelligence by far. It teaches you modern algorithms. I really like it. Great value.Published on April 30, 2013 by reviewer
I enjoyed this book. It is written at a level that can sink my teeth into without too much concentration on statistical mathematical equations all over the page. Read morePublished on March 1, 2010 by Patrick E. Martin
This book gave me a head start on AI with hands-on examples on different techniques I could use in many different problems. Read morePublished on November 30, 2008 by Alireza Goudarzi
It's just amazing how such a 473-page book could cover wide range of AI subjects, and at the same time could deliver easy-to-understand explanations without throwing PhD maths at... Read morePublished on October 8, 2007 by Neo Lee
I feel bad saying this, but -- the book's goals and structure are great, and the author definitely put in a good effort to make this book. Read morePublished on September 2, 2007 by J. King
It is the best introductory book on AI. As you can read from other reviewer's with low rating, it's not in depth. Read morePublished on August 23, 2007 by Anonymous
This book covers a good range of topics but fails to deliver the topics in a clear and concise manner. Read morePublished on April 21, 2007 by Sean Todd
One of the challenges in learning AI are the foundational requirements in mathematics. This book provides an excellent introduction to AI, where the "hacker" or hobbyist can... Read morePublished on March 6, 2007 by Robert