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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We distinguish two major kinds of control strategies: irrevocable and tentative. In an irrevocable control regime, an applicable rule is selected and applied irrevocably without provision for reconsideration later.
In the second type of tentative control regime, which we call graph-search control, provision is made for keeping track of the effects of several sequences of rules simultaneously. Various kinds of graph structures and graph searching ...
Even though the control strategy cannot always select the best rule to apply at any stage, there are times where an irrevocable regime is appropriate. For example, if the application of what might turn out to be an inappropriate rule ...
The backtracking process is one way in which the control strategy can be tentative. ... Whereas hill-climbing with an irrevocable control regime might get stuck on local maxima, backtracking allows alternative paths to be pursued.
8 2 l (6) 8 2 1 (7) 8 2 Suppose we decide to use a graph-search control regime in. # | | | : | | & | : # ; | 4 7| 5 (5) # | | # 4 7|5 | # # : 6 (3) 8 2 1 Q) 8 2 7|5 7 : 6 4 7|5 Again, we have applied six rules without reaching a goal, ...
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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 |