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
Results 1-5 of 31
... 8-puzzle. The 8-puzzle consists of eight numbered, movable tiles set in a 3 X 3 frame. One cell of the frame is always empty thus making it possible to move an adjacent numbered tile into the empty cell—or, we could say, to move the ...
... 8 down, ..., etc.” To solve a problem using a production system, we must specify the global database, the rules, and the control strategy. Transforming a problem statement into these three components of a ... 8-puzzle. 19 PRODUCTION SYSTEMS.
... 8-puzzle is conveniently interpreted as having the following four moves: Move empty space (blank) to the left, move blank up, move blank to the right, and move blank down. These moves are modeled by production rules that operate on the ...
... 8-puzzle we might use, as a function of the state description, the negative of the number of tiles “out of place ... puzzle. The value of our hill-climbing function for each state description is circled. The figure shows that one of the ...
Nils J. Nilsson. For the instance of the 8-puzzle in Figure 12, the hill-climbing strategy allowed us to find a path to a goal state. In general, however, hill-climbing functions can have multiple local maxima, which frustrates hill ...
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 |