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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A further generalization is to specify some true / false condition on states to serve
as a goal condition . Then the goal would be to achieve any state satisfying this
condition . Such a condition implicitly defines some set of goal states .
If the applicability conditions of the rules involve tests on individual atoms only ,
and if the effects of the rules are to substitute a qualifying ... In order to
decompose a database , we must also be able to decompose the termination
The second set , Ajj , computed for the condition Cij , is the set of F - rules
specified by the graph that add Cij and are not ancestors of rule j in the graph nor
j itself . This set is called the adders of Cij . Any adder of Cij is important because
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