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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... solution to a programming or robot control problem and then modify it (to make it work correctly), than to insist on a first solution ... graph containing n nodes such that the path visits each of the n nodes precisely once. Many puzzles have ...
... solution, the state of the computation reverts to the previous backtracking point, where another rule is applied instead, and the process continues. In the second type of tentative control regime, which we call graph-search control ...
... solution, the intervening steps are “forgotten,” and another rule is selected instead. Formally, the backtracking ... Graph Search. Graphs (or more specially, trees) are extremely useful structures for keeping track of the effects of ...
Nils J. Nilsson. Suppose we decide to use a graph-search control regime in solving the ... graph-search control regimes, it is useful to notice that an irrevocable ... solution requires more than an efficient control strategy. It requires ...
... naming all of the other cities satisfies the termination condition. Notice that we can use the. Fig. 1.6 A search tree for the traveling salesman problem. Fig. 1.8 Equivalent paths in a graph. Fig. 1.9 Solution. 30 PRODUCTION SYSTEMS AND ...
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 |