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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The various rules that can be applied correspond to links or directed arcs to descendant nodes, ... control strategy would grow a much narrower tree, using its special knowledge to focus the growth more directly toward the goal.
We call the set {t} the goal set, and each node t in (t; } is a goal node. A graph may be specified either explicitly or implicitly. In an explicit specification, the nodes and arcs (with associated costs) are explicitly given by a ...
operator that is applied to a node to give all of the successors of that node (and the costs of the associated arcs). ... can be viewed as a process of making explicit a portion of an implicit graph sufficient to include a goal node.
Whenever the node selected for expansion is a goal node, the process terminates successfully. The successful path from start node to goal node can then be recovered (in reverse) by tracing the pointers back from the goal node to s.
(The process can be made to terminate virtually as soon as a goal node is generated by putting goal nodes at the very beginning of OPEN; but, of course, this procedure would involve a goal test during step 8 of.
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Contents
| 1 | |
| 17 | |
| 53 | |
CHAPTER 3 SEARCH STRATEGIES FOR DECOMPOSABLE PRODUCTION SYSTEMS | 99 |
CHAPTER 4 THE PREDICATE CALCULUS IN AI | 131 |
CHAPTER 5 RESOLUTION REFUTATION SYSTEMS | 161 |
CHAPTER 6 RULEBASED DEDUCTION SYSTEMS | 193 |
CHAPTER 7 BASIC PLANGENERATING SYSTEMS | 275 |
CHAPTER 8 ADVANCED PLANGENERATING SYSTEMS | 321 |
CHAPTER 9 STRUCTURED OBJECT REPRESENTATIONS | 361 |
PROSPECTUS | 417 |
BIBLIOGRAPHY | 429 |
AUTHOR INDEX | 467 |
SUBJECT INDEX | 471 |
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Bibliographic information
| Title | Principles of Artificial Intelligence |
| Author | Nils J. Nilsson |
| Edition | reprint |
| Publisher | Morgan Kaufmann, 2014 |
| ISBN | 1483295869, 9781483295862 |
| Length | 476 pages |
| Subjects | › Computers / General |
| Export Citation | BiBTeX EndNote RefMan |