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 327
Since the last F - rule to be applied , stack ( A , B ) , was also the rule that
achieved ON ( A , B ) , RSTRIPS regresses ON ... In this case , the subgoal was
not changed by regression , and RSTRIPS now attempts to achieve this
regressed goal at ...
Since the last F - rule to be applied , stack ( A , B ) , was also the rule that
achieved ON ( A , B ) , RSTRIPS regresses ON ... In this case , the subgoal was
not changed by regression , and RSTRIPS now attempts to achieve this
regressed goal at ...
Page 350
Once a plan has been developed to achieve the high - level conditions ( and their
high - level preconditions , and so on ) , other steps can be added in place to the
plan to achieve lesser conditions , and so on . This method does not require ...
Once a plan has been developed to achieve the high - level conditions ( and their
high - level preconditions , and so on ) , other steps can be added in place to the
plan to achieve lesser conditions , and so on . This method does not require ...
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Contents
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
SEARCH STRATEGIES FOR DECOMPOSABLE | 99 |
Copyright | |
10 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 evaluation example expression F-rule fact Figure formula function given goal 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 search tree selected sequence shown in Figure simple solution graph solve specify statement step STRIPS structure subgoal substitutions successors Suppose symbols termination theorem tree 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 |