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
( The function k is undefined for nodes having no path between them . ) The cost
of a minimal cost path from node n to some particular goal node , ti , is then given
by k ( n , t ; ) . We let h * ( n ) be the minimum of all of the k ( n , ti ) over the entire ...
( The function k is undefined for nodes having no path between them . ) The cost
of a minimal cost path from node n to some particular goal node , ti , is then given
by k ( n , t ; ) . We let h * ( n ) be the minimum of all of the k ( n , ti ) over the entire ...
Page 122
We repeat part of this tree in Figure 3.11 . Suppose that search had progressed in
a depth - first manner and that whenever a tip node is generated , its static
evaluation is computed . Also suppose that whenever a position can be given a ...
We repeat part of this tree in Figure 3.11 . Suppose that search had progressed in
a depth - first manner and that whenever a tip node is generated , its static
evaluation is computed . Also suppose that whenever a position can be given a ...
Page 313
Representing what would normally be relations as individuals is a way of gaining
some of the benefits of a higher order logic in a first - order formulation . The
initial state shown in Figure 7.11 is then given by the following set of expressions
: 1 ...
Representing what would normally be relations as individuals is a way of gaining
some of the benefits of a higher order logic in a first - order formulation . The
initial state shown in Figure 7.11 is then given by the following set of expressions
: 1 ...
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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 global database 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 |