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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Now we consider the process of applying a rule of the form ( L W ) to an AND /
OR graph , where L is a literal , W is a wff in AND / OR form , and all expressions
might contain variables . The rule is applicable if the AND / OR graph contains a ...
ABSTRIPS begins by considering only conditions of highest criticality , namely ,
those with criticality value 3 in this example . ... Since our main goal contains two
conditions of value 3 , ABSTRIPS considers one of them , say , ON ( C , B ) , and ...
Before talking about how implications are used in general , we consider a
frequently occurring special use : when an implication asserts properties about
every member of a given set . Consider , for example , the sentence “ All
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