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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Goal literals ( as well as rules ) can be used to add descendants to the AND / OR
graph . When one of the goal literals matches a literal labeling a literal node , n ,
of the graph , we add a new descendant of node n , labeled by the matching ...
This expression , in turn , corresponds to the solution graph terminating in the
literal nodes labeled by R ( A ) and Q ( x ) . ... When a goal literal , L , unifies with
a literal L ' labeling a literal node , n , of the graph , we can add a match arc ...
Such a B - rule is applicable to an AND / OR graph representing a goal wff if that
graph contains a literal node labeled by L ' that unifies with L . The result of
applying the rule is to add a match arc from the node labeled by L ' to a new ...
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