The fifth edition of this book continues to provide a balanced perspective on the language schools, theories, and applications of artificial intelligence. These diverse branches are unified through detailed discussions of AI’s theoretical foundations. The book is broken down into six parts to provide readers complete coverage of AI. It begins by introducing AI concepts, moves into a discussion on the research tools needs for AI problem solving, and then demonstrates representations for AI and knowledge-sensitive problem solving. The second half of the book offers an extensive presentation of issues in machine learning, continues presenting important AI application areas, and presents Lisp and Prolog to the reader. This book is appropriate for programmers both as an introduction to and a reference of the theoretical foundations of artificial intelligence.
New to this edition
* Brand new chapter which introduces the stochastic methodology.
* Extended material in many sections addresses the continuing importance of agent-based problem solving and embodiment in AI technology.
* Presentation of issues in natural language understanding, including sections on stochastic methods for language comprehension; Markov models; CART trees; mutual information clustering; and statistic based parsing.
* Further discussion of the AI endeavor from the perspectives of philosophy, psychology, and neuro-psychology.
Artificial Intelligence: Structures and Strategies for Complex Problem Solving is ideal for a one or two semester university course on AI, as well as an invaluable reference for researchers in the field or practitioners wishing to employ the power of current AI techniques in their work.
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