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 figure shows that one of the rule applications along the path did not increase the value of our function. If none of the applicable rules permits an increase in the value of our function, a rule is selected ...
Thus, the use of hill-climbing methods to guide rule selection in irrevocable production systems is quite limited. Even though the control strategy cannot always select the best rule to apply at any stage, there are times where an ...
A rule is selected, and if it doesn't lead to a solution, the intervening steps are “forgotten,” and another rule is ... strategy can be used regardless of how much or how little knowledge is available to bear on rule selection.
It requires selecting good representations for problem states, moves, and goal conditions. The representation of a problem has a great influence on the effort needed to solve it. Obviously one prefers representations with small state ...
For any D* selected, though, it need only select one applicable rule. Even though processing component databases in parallel is possible, we are typically interested in control strategies that process them in ...
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Contents
| 1 | |
| 17 | |
CHAPTER 2 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS | 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 |