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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First , it terminates successfully ( in step 1 ) only if it produces a database
satisfying the termination condition . The list of rules used in producing this
database is built up in step 10 . Unsuccessful terminations can occur in steps 2
and 4 .
Each node in G is also in T . The search tree is defined by the pointers that are
set up in step 7 . Each node ( except s ) in G has a pointer directed to just one of
its parents in G , which defines its unique parent in T . Each possible path to a
summing the arc costs encountered while tracing the pointers from n to s . ( This
path is the lowest cost path from s to n found so far by the search algorithm . The
value of g ( n ) for certain nodes may decrease if the search tree is altered in step
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