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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Specify a nine - dimensional vector w , such that the dot product cow is a useful
evaluation function for use by MAX ( playing Xs ) to evaluate nonterminal
positions . Use this evaluation function to perform a few minimax searches
making any ...
To specify a syntax we must specify the alphabet of symbols to be used in the
language and how these symbols are to be put together to form legitimate
expressions in the language . The legitimate expressions of the predicate
calculus are ...
B - rule , the domain expert may want to specify the order in which the subgoals
should be attacked . For each of these subgoals , he may further want to specify
explicitly a set of B - rules to be used on them and the order in which these B ...
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