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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... match . There might be a match against F1 , so we check to see if cons ( 1 , cons ( 2 , NIL ) ) unifies with NIL . [ Compare with if null ( x ) in the program . ] Failing this test , we check for a match against the consequent of R2 ...
... match can be found , we say that the precondition of the F - rule matches the facts . We call the unifying composition , the match substitution . For a given F - rule and state description , there may be many match substitutions . Each ...
... match is successful in Figure 9.10 , but it is unsuccessful in Figure 9.11 . In any representational scheme there are often several alternative representations for basically the same information . Since our definition of structure matching ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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