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 75
That is , f ( n ) is an estimate of the cost of a minimal cost path constrained to go through node n . ... n Often we are interested in knowing the cost k ( s , n ) of an optimal path from a given start node , s , to some arbitrary node ...
That is , f ( n ) is an estimate of the cost of a minimal cost path constrained to go through node n . ... n Often we are interested in knowing the cost k ( s , n ) of an optimal path from a given start node , s , to some arbitrary node ...
Page 77
S Let d * ( n ) be the length of the shortest path in the implicit graph being searched from s to any node n in the search tree produced by A * . Then since the cost of each arc in the graph is at least some small positive number e ...
S Let d * ( n ) be the length of the shortest path in the implicit graph being searched from s to any node n in the search tree produced by A * . Then since the cost of each arc in the graph is at least some small positive number e ...
Page 78
But the f * value of any node on an optimal path is equal to f * ( s ) , the minimal cost , and therefore f ( n ' ) = f * ( s ) . Thus , we have : RESULT 2 : a At any time before A * terminates , there exists on OPEN a node n ' that is ...
But the f * value of any node on an optimal path is equal to f * ( s ) , the minimal cost , and therefore f ( n ' ) = f * ( s ) . Thus , we have : RESULT 2 : a At any time before A * terminates , there exists on OPEN a node n ' that is ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
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 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 |