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 Nodes Rules : А эслD BEAG Fact ( A V B ) Fig . 6 . 4 An AND / OR graph
satisfying termination . simple goal expressions . ) Goal literals ( as well as rules )
can be used to add descendants to the AND / OR graph . When one of the goal ...
We first encounter GOAL ( BOSSOF ? u ? v ) . Since no facts match this goal , we
look for B - rules and find BR1 . The pattern match merely passes along the
existential variables . The computational environment is now as shown in Figure
First , it must decide how to order the components of a compound goal above the
compound goal in the goal stack . A reasonable approach is first to find all of
those components that match the current state description . ( Conceptually , they
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