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 . That node on OPEN having the smallest value of f is then the
node estimated to impose the least severe constraint ; hence it is appropriate that
it ...
That is , f ( n ) is an estimate of the cost of a minimal cost path constrained to go
through node n . That node on OPEN having the smallest value of f is then the
node estimated to impose the least severe constraint ; hence it is appropriate that
it ...
Page 102
( These costs model the costs of rule applications ; again we need to assume that
each cost is greater than some small positive number , e . ) The connector costs
can then be used to calculate the cost of a solution graph . Let the cost of a ...
( These costs model the costs of rule applications ; again we need to assume that
each cost is greater than some small positive number , e . ) The connector costs
can then be used to calculate the cost of a solution graph . Let the cost of a ...
Page 106
newly computed costs of its successors ) and marks the outgoing connector on
the estimated best " path " to terminal nodes . This revised cost estimate is
propagated upward in the graph . ( Acyclicity of our graphs guarantees no loops
in this ...
newly computed costs of its successors ) and marks the outgoing connector on
the estimated best " path " to terminal nodes . This revised cost estimate is
propagated upward in the graph . ( Acyclicity of our graphs guarantees no loops
in this ...
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Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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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 global database 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 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