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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... discussed in chapter 4. As an example , consider the robot hand and configuration of blocks shown in Figure 7.1 . This situation can be represented by the conjunction of formulas shown in the figure . The formula CLEAR ( B ) means that ...
... discussed in McCarthy and Hayes ( 1969 ) , Hayes ( 1973a ) , and Raphael ( 1971 ) . The problem of dealing with anomalous conditions is discussed in McCarthy and Hayes ( 1969 ) and in McCarthy ( 1977 ) . McCarthy calls this problem the ...
... discussed in that paper . The use of regression for computing the effects of B - rules is based on a similar use by Waldinger ( 1977 ) . The STRIPS problem - solving system is described in Fikes and Nilsson ( 1971 ) . The version of ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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