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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... 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 , by adding R to the front of the list . We ...
... 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 back to ...
... recursive GPS is very similar to ( if slightly more general than ) recursive STRIPS . ( Historically , the design of STRIPS was motivated by GPS . ) The program for recursive GPS might look something like the following : First , we set ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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