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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Computational theorists rank the difficulty of various problems on how the worst
case for the time taken ( or number of steps taken ) using the theoretically best
method grows with some measure of the problem size . ( For example , the
These methods are illustrated by considering simple problems in robot planning
and automatic programming . Chapter 7 introduces some of the more basic ideas
, and chapter 8 elaborates on the subjects of complex goal interactions and ...
HEURISTIC GRAPH - SEARCH PROCEDURES The uninformed search methods
, whether breadth - first or depth - first , are exhaustive methods for finding paths
to a goal node . In principle , these methods provide a solution to the path ...
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