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 problem generalizes to one of finding a minimum cost path over the edges of a graph containing n nodes such that the path visits each of the n nodes precisely once. Many puzzles have this same general character.
In general we ascribe a cost to each move and then attempt to find a solution having minimal cost. These elaborations can easily be handled by methods we describe later on. 1.1.2. THE BASIC PROCEDURE The basic production system ...
1 + 22 1 + 22 2 = tan w | f : 7. Jas The nodes of the tree represent expressions to be integrated. Fig. 1.13 An AND/OR tree for an integration problem. Fig. 2. 1 Computational costs of AI production systems.
A completely uninformed control system incurs only a small control strategy cost because merely arbitrary rule ... However, such a strategy results in high rule application costs because it generally needs to try a large number of rules ...
Control strategy cost Rule application cost O —l 0 “Informedness” COMPLETE Completely informed control strategies, however, result in minimal rule application costs; they guide the production system directly to a solution.
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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 |