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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operator that is applied to a node to give all of the successors of that node ( and
the costs of the associated arcs ) . We call this process of applying the successor
operator to a node , expanding the node . The successor operator depends in an
When node 1 is expanded , its single successor , node 2 , is generated . But node
2 , with parent node 3 in the search tree , had previously been generated , and
node 2 is also on CLOSED with successor nodes 4 and 5 . Note , however , that ...
Suppose a tree has depth D , and every node ( except a tip node ) has exactly B
successors . Such a tree will have precisely BD tip nodes . Suppose an alpha -
beta procedure generated successors in the order of their true backed - up
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