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 Intelligence"evolved 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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8 PATH - BACKTRACK ( RDATA ) ; BACKTRACK is called recursively on the new
database . 9 if PATH = FAIL , go LOOP ; if the recursive call fails , try another rule .
10 return CONS ( R , PATH ) ; otherwise , pass the successful list of rules up ...
Note that the recursive algorithm does not remember all databases that it visited
previously . Backtracking involves " forgetting ” all databases whose paths lead to
failures . The algorithm remembers only those databases on the current path ...
Once an F - rule was selected as relevant to removing a difference , GPS worked
recursively on the preconditions for that F - rule . ... Thus , we see that recursive
GPS is very similar to ( if slightly more general than ) recursive STRIPS .
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