This book presents both theoretical foundations of AI and an indication of the ways that current techniques can be used in application programs. With the revision, most of the content has been preserved as it is, and an effort has been put in on adding new topics that are in sync with the recent developments in this field. Key Features: Four new chapters added that discusses recent advancements in Genetic Algorithms, Artificial Immune Systems, and Agents PROLOG being one of the popular languages for AI programming has been added in the form of a new chapter. Knowledge Representation, syllabus relevant topic, covered in a separate section (spanned over 8 chapters) All important Heuristic Techniques, including Hill Climbing, BFS, and Generate and Test have been covered explicitly An exhaustive OLC in the face of none provided by competing titles Pedagogy Review Questions: 161 Illustrations: 279 Recent advancements in AI elucidated in the form of four new chapters Heuristic techniques given added emphasis Case Studies on Network Security, Robot Control and Navigation Popular Languages such as LISP and PROLOG are covered Table of Content: PART I: PROBLEMS AND SEARCH Chapter 1. What is Artificial Intelligence? Chapter 2. Problems, Problem Spaces, and Search Chapter 3. Heuristic Search Techniques PART II: KNOWLEDGE REPRESENTATION Chapter 4. Knowledge Representation Issues Chapter 5. Using Predicate Logic Chapter 6. Representing Know
The standard AI text is Artificial Intelligence: A Modern Approach by Russell and Norvig, but I'd like to argue that Elaine Rich's AI book is better in many ways.
First, it is shorter, and it covers less. While that makes it less suitable as a desk reference than the Russell/Norvig book, it makes it perhaps better as an introductory text, as it's a bit more focused, more content to cover "core" AI rather than comprehensively cover every aspect of the field like Russell/Norvig.
Second, and this may run counter to what a lot of people may say, but frankly the Rich book is simply more readable. She's a better writer overall, and lays out the material in a way that I think is more instructive and more informative. I think that, as an introductory text, this book works much better than Russell/Norvig. Despite Russell/Norvig devoting more overall text to explaining any given topic, I think Rich's coverage of the same material tends to be clearer.
There's no denying that nothing is going to knock Russell/Norvig from it's throne any time soon, but I have to suggest for any professor teaching an introductory AI class to at least consider Rich's book, which as a student I found helped me with the material much more than A Modern Approach.
I've seen a lot of complaints about this book being overly formal, grounded in theoretical material too much. As a theory-focused student, I actually liked that, and I think a lot of the complaints are from students who just wanted to build Quake bots or something. Besides, Russell/Norvig is just as formal, if not more so.