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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... discussed by Gardner (1964, 1965a,b,c) and by Ball (1931, pp. 224-228). The traveling-salesman problem arises in operations research [see Wagner (1975), and Hillier and Lieberman (1974)]. A method for finding optimal tours has been ...
... discussed the hill-climbing method of irrevocable rule selection, exploring a surface for a maximum, and the backtracking and graphsearch regimes, search processes that permitted tentative rule selection. Our main concern in the present ...
... discussed.) The algorithm must now attempt to place a queen in row 6. Note that no cell in row 6 is satisfactory; each attempt to place a queen in that row would fail. In such a circumstance, BACKTRACK would attempt to relocate the ...
... (discussed below) or on various arbitrary criteria. Whenever the node selected for expansion is a goal node, the process terminates successfully. The successful path from start node to goal node can then be recovered (in reverse) by ...
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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 |