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 240
An alternative treatment of a goal of the form P1 → P2 involves converting this goal to the subgoal P2 while adding Pl to the set of facts that can be used in proving P2 or its subgoals . Then , if the system generates Pl as a subgoal ...
An alternative treatment of a goal of the form P1 → P2 involves converting this goal to the subgoal P2 while adding Pl to the set of facts that can be used in proving P2 or its subgoals . Then , if the system generates Pl as a subgoal ...
Page 288
Our first step in designing a backward production system is to specify a set of B - rules that transform goal expressions into subgoal expressions . One strategy is to use B - rules that are based on the F - rules that we have just ...
Our first step in designing a backward production system is to specify a set of B - rules that transform goal expressions into subgoal expressions . One strategy is to use B - rules that are based on the F - rules that we have just ...
Page 292
In this particular example , the subgoal space generated by applying all applicable B - rules is larger than the state space that we produced using F - rules . Many of the subgoal descriptions , however , are " impossible , " that is ...
In this particular example , the subgoal space generated by applying all applicable B - rules is larger than the state space that we produced using F - rules . Many of the subgoal descriptions , however , are " impossible , " that is ...
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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 |