Principles of Artificial Intelligence
A classic introduction to artificial intelligence intended to bridge the gap between theory and practice, Principles of Artificial Intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval. Rather than focusing on the subject matter of the applications, the book is organized around general computational concepts involving the kinds of data structures used, the types of operations performed on the data structures, and the properties of the control strategies used.
Principles of Artificial Intelligenceevolved from the author's courses and seminars at Stanford University and University of Massachusetts, Amherst, and is suitable for text use in a senior or graduate AI course, or for individual study.
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... representations are still poorly understood . It seems that desirable shifts in a problem's representation depend on experience gained in attempts to solve it in a given representation . This experience allows us to recognize the ...
... representation for a set of clauses . [ The AND / OR graph representation for an expression is actually slightly less general than the clause representation , however , because not multiplying out common subexpressions can prevent ...
... representation , the system designer must also decide on how predicate calculus expressions are to be encoded in ... representation used in large AI systems . In this chapter , we describe some of the specialized representations that ...
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