Principles of Artificial IntelligenceA 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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... value , while positions favorable to MIN cause the evaluation function to have a negative value ; values near zero ... backed - up value equal to the maximum of the evaluations of the tip nodes . On the other hand , if MIN were to choose ...
... backed - up value of - ∞ and proceed with the search , having saved the search effort of generating and evaluating nodes B , C , and D. ( Note that the savings in search effort would have been even greater if we were searching to ...
Nils J. Nilsson. backed - up values , the bounds on backed - up values can be revised . But we note that : ( a ) The ... value less than or equal to the alpha value of any of its MAX node ancestors . The final backed - up value of this ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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