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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Part of a search tree for this problem is shown in Figure 1.7. In this simple example, aside from different possible orderings of rule applications, there is very little branching in the tree. 1.1.7.
DET N P DET A N V DET N | i DNP P DNP VP Another sequence produces the following string: DNP P S DNP PP VP Nothing more can be done to this string DNP VP Goal Fig. 1.7 A search tree for the syntax analysis problem.
Now consider another production system whose global database is the entire search tree of the first. The rules of the new production system represent the various ways in which a search tree can be modified by the action of the control ...
... B, M) and whose termination condition is that the database contain only Ms. Agraph-search control regime might ... (Many of the rule applications in the right-hand branch of the tree in Figure 1.9 are ones needed in a solution.) ...
In Figure 1.13 we show an AND/OR tree that illustrates a possible search performed by a decomposable production system. The problem is to integrate 4 | —-ax (1 - x2)” Algebraic substitutions Example x*dx - !
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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 |