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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A Backward Deduction System 212 3. “Resolving” Within AND/OR Graphs 234 4. Computation Deductions and Program Synthesis 241 6.5. A Combination Forward and Backward System 253 6.6. Control Knowledge For Rule-Based Deduction Systems 257 ...
BACKWARD AND BIDIRECTIONAL PRODUCTION SYSTEMS We might say that our production system for solving the 8-puzzle worked forward from the initial state to a goal state. Thus, we could call it a forward production system.
We could also have solved the problem in a backward direction, by starting at the goal state, applying inverse moves, and working toward the initial state. Each inverse move would produce a subgoal state from which the immediately ...
Although there is no formal difference between a production system that works on a problem in a forward direction and one that works in a backward direction, it is often convenient to make this distinction explicit.
Depending on the way a problem is represented for solution by a production system, either of these types might be used in a forward or backward direction. They might be controlled by irrevocable or tentative control regimes.
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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 |