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
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... knowledge about the problem being solved so that the rule selected in step 4 has a good chance of being the most appropriate one. We distinguish two major kinds of control strategies: irrevocable and tentative. In an irrevocable control ...
... knowledge, about how to proceed toward a goal from any state, and the implicit global knowledge, of the complete solution. When infallible local knowledge is available, an irrevocable production system can use it to construct the ...
... knowledge is available to bear on rule selection. If no knowledge is available, rules can be selected according to some arbitrary scheme. Ultimately, control will backtrack to select the appropriate rule. Obviously, if good rule ...
... knowledge to focus the growth more directly toward the goal. We shall be discussing several methods for achieving such focusing in chapter 2. Even though we use graphs of this sort only with graph-search control regimes, it is useful to ...
... knowledge as well as features of the mass spectrogram.) The initial database is simply the formula C5H12. In this case, the rules propose the following partial structures: |C, H, H " H | - - - - | H – C – H H : H C = C | |C, H, - Č–H ...
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 |