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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CHAPTER 5 RESOLUTION REFUTATION SYSTEMS In this chapter and chapter
6 , we are primarily concerned with systems that prove theorems in the predicate
calculus . Our interest in theorem proving is not limited to applications in ...
PRODUCTION SYSTEMS FOR RESOLUTION REFUTATIONS We can think of a
system for producing resolution refutations as a production system . The global
database is a set of clauses , and the rule schema is resolution . Instances of this
The set - of - support , linear - input form , and ancestry - filtered form strategies
restrict resolutions . Of all the resolutions ... This fact does not mean , however ,
that resolution order has no effect on the efficiency of the process . On the
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PRODUCTION SYSTEMS AND AI
SEARCH STRATEGIES FOR
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