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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These rules are to be applied to a global database consisting of a set of symbols .
A rule is applicable if the global database contains a symbol matching its left -
hand side . The effect on the global database of applying the rule is to remove the
We might use the predicate symbol WRITE to denote a relationship between a
person doing the writing and a thing written . We can compose a ... In general ,
atomic formulas are composed of predicate symbols and terms . A constant
symbol . ( Examples : WRITE , MARRIED . ) In some abstract examples , short
strings of upper - case letters and numerals ( P1 , Q2 ) are used as predicate
symbols . A mnemonic string of capital letters or short strings of upper - case
letters and ...
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