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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... backed - up value . The utility of this whole procedure rests on the assumption that the backed - up values of the start node's successors are more reliable measures of the ultimate relative worth of these positions than are the values ...
... backed - up values of the other successors of the start node , the final backed - up value of the start node may be greater than 1 , but it cannot be less . We call this lower bound an alpha value for the start node . - - Now let depth ...
Nils J. Nilsson. backed - up values , the bounds on backed - up values can be revised . But we note that : ( a ) The alpha values of MAX nodes ( including the start node ) can never ... ( Backed - Up Value = +1 ) 123 SEARCHING GAME TREES.
PRODUCTION Systems and AI
SEARCH Strategies FOR
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