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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that node in the graph labeling the entire fact expression , the root node . It has
no ancestors in the graph . An interesting property of the AND / OR graph
representation of a wff is that the set of clauses into which that wff could have
Usually , we draw our AND / OR graph representations of fact expressions “
upside down . ” Later we also use AND / OR graph representations of goal wffs ;
these are displayed in the usual manner , “ rightside up . ” When we represent
wffs by ...
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 ...
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