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. |
From inside the book
Results 1-5 of 73
... shown in Figure 1.1. We can also deal with problems for which the goal is to achieve any one of an explicit list of problem states. A further generalization is to specify some true/false condition on states to serve as a goal condition ...
... shown in the map of Figure 1.5. There is a road between every pair of cities, and the distance is given next to the road. Starting at city A, the problem is to find a route of minimal distance that visits each of the cities only once ...
... given string of symbols that we want to test. The production rules are derived from the rewrite rules of the grammar ... shown in Figure 1.7. In this simple example, aside from different possible orderings of rule applications, there is ...
... Figure 1.8 we have three rules, R1, R2, and R3, that are applicable to the database denoted by SO. After applying ... shown. Methods for avoiding exploration of redundant paths are obviously of great importance for commutative systems ...
... shown in Figure 1.9. Redundant paths can lead to inefficiencies because the control strategy might attempt to explore all of them, but worse than this, in exploring paths that do not terminate successfully, the system may nevertheless ...
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 |
Other editions - View all
Common terms and phrases
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 / Artificial Intelligence / Expert Systems Computers / Artificial Intelligence / General Computers / Data Science / General Computers / General |
| Export Citation | BiBTeX EndNote RefMan |