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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PRSTRIPsect of applyndo 8 . 2 . DCOMP We call our next system for dealing with
interacting goals DCOMP . It operates in two main phases . In phase 1 , DCOMP
produces a tentative “ solution , ” assuming that there are no goal interactions .
3 , we show a possible DCOMP first - phase solution with the adders and deleters
listed for each condition . Note that , compared with Figure 8 . 2 , there are fewer
deleters of the HANDEMPTY predicates because we have two hands . During ...
... 11 - 15 Atomic formulas , in predicate calculus , 132 Attachment , procedural ,
173 - 174 , 232 , 234 , 400 - 401 Automatic programming , 5 - 6 by DCOMP , 348 -
349 references for , 14 , 269 by resolution , 191 by RSTRIPS , 331 - 333 by rule ...
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