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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For the 8-puzzle, a straightforward description is a 3 X 3 array or matrix of numbers. The initial global database is this description of the initial problem state. Virtually any kind of data structure can be used to describe states.
These moves are modeled by production rules that operate on the state descriptions in the appropriate manner. ... language of states, moves, and goals, a solution to a problem is a sequence of moves that transforms an initial state into ...
For example, the value of this function for the initial state in Figure 1.1 is –4, and the value for the goal state is 0. We can easily compute the value of this function for any state description. From the initial state, ...
For example, suppose the goal state is 1 2 3 74 86 5 and the initial state is 1 2 5 74 86 3 Any applicable rule applied to the initial state description lowers the value of our hill-climbing function. In this case the initial state ...
Backing up will occur (a) whenever we generate a state description that already occurs on the path back to the initial state description, (b) whenever we have applied an arbitrarily set number of rules without having generated a goal ...
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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 |