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 Intelligenceevolved 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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... 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 . Goal expressions are ...
... 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 the second phase of ...
... DCOMP , 336 Admissibility , of search algorithms , 76 Advice , added to delineations , 406-408 AI languages , 261 references for , 267 , 270 , 417 , 418 Alpha - beta procedure , for games , 121- 126 efficiency of , 125-126 references ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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