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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Nodes labeled by compound databases have sets of successor nodes each labeled by one of the components. These successor nodes are called AND nodes because in order to process the compound database to termination, all of the component ...
Nodes labeled by these component databases have successor nodes labeled by the results of rule applications. These successor nodes are called OR nodes because in order to process a component database to termination, the database ...
If an arc is directed from node n, to node n, then node n; is said to be a successor of node n, and node n, is said to be aparent of node n, . In the graphs that are of interest to us, a node can have only a finite number of successors.
A node in the tree having no successors is called a tip node. ... A sequence of nodes (nii, nig,..., nik), with each ni; a successor of ni, -, for j = 2,..., k, is called a path of length k from node ni, to node nik.
operator that is applied to a node to give all of the successors of that node (and the costs of the associated arcs). We call this process of applying the successor operator to a node, expanding the node. The successor operator depends ...
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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 |