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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... domain ; to each constant symbol , an entity in the domain ; and to each function symbol , a function in the domain . These assignments define the semantics of the predicate calculus language . In our applications , we are using the ...
... domain . The formula consisting of the existential quantifier ( 3x ) in front of a formula P ( x ) has value T for an interpretation just when the value of P ( x ) under the interpretation is T for at least one assignment of x to an ...
... domain in which the AI program is to operate . It is often just as important for the physicians , chemists , and other domain experts to supply control knowledge as it is for them to supply declarative and procedural knowledge . There ...
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