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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... sequence composed of rules that are applicable to D is invariant under permutations of the sequence . The rule applications in Figure 1.8 possess this commutative property . In producing the database denoted by SG in Figure 1.8 , we ...
... sequence . Let the top row be called the first row . If there are N F - rules in the plan sequence , then the last row is the ( N + 1 ) -th row . The entries in cell ( i , j ) of the table , for j > 0 and i < N + 1 , are those literals ...
... sequence of F - rules applied so far . From this sequence of F - rules , RSTRIPS can always compute what the state description would be if this sequence were applied to the initial state . Actually , RSTRIPS never needs to compute such ...
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