Principles of Artificial IntelligenceA 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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Page 20
We can also deal with problems for which the goal is to achieve any one of an
explicit list of problem states . A further generalization is to specify some true /
false condition on states to serve as a goal condition . Then the goal would be to
...
We can also deal with problems for which the goal is to achieve any one of an
explicit list of problem states . A further generalization is to specify some true /
false condition on states to serve as a goal condition . Then the goal would be to
...
Page 291
The regression of HANDEMPTY through unstack ( x , A ) is F . Since no
conjunction containing F can be achieved , we see ... Checking for the
consistency of goals is important in order to avoid wasting effort attempting to
achieve those that are ...
The regression of HANDEMPTY through unstack ( x , A ) is F . Since no
conjunction containing F can be achieved , we see ... Checking for the
consistency of goals is important in order to avoid wasting effort attempting to
achieve those that are ...
Page 293
5 Part of the backward ( goal ) search graph for a robot problem . attempting to
achieve it when it occurs in subgoal descriptions . ( Sometimes , of course , goal
literals that already match literals in the initial state might get deleted by early F ...
5 Part of the backward ( goal ) search graph for a robot problem . attempting to
achieve it when it occurs in subgoal descriptions . ( Sometimes , of course , goal
literals that already match literals in the initial state might get deleted by early F ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
9 other sections not shown
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Common terms and phrases
achieve actions algorithm AND/OR graph answer applied arcs Artificial Intelligence assume attempt backtracking backward block called chapter clause CLEAR(C complete component condition consider consistent contains control strategy corresponding cost database deduction Deleters described direction discussed efficient evaluation example expression F-rule fact Figure formula function given goal goal node goal stack goal wff HANDEMPTY heuristic important initial involves JOHN knowledge labeled language literals logic match methods move namely node Note obtained occur ONTABLE(A operation path possible precondition predicate calculus problem procedure production system proof prove quantified reasoning refutation represent representation resolution result robot rule satisfied selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem unifying unit University variables
Bibliographic information
| Title | Principles of Artificial Intelligence Symbolic computation |
| Author | Nils J. Nilsson |
| Edition | illustrated |
| Publisher | Tioga Publishing Company, 1980 |
| Original from | the University of Michigan |
| Digitized | 15 Nov 2007 |
| ISBN | 0935382011, 9780935382013 |
| Length | 476 pages |
| Export Citation | BiBTeX EndNote RefMan |