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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... Historical Remarks 48 Exercises 50 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS 53 Backtracking Strategies 55 Graph-search Strategies 61 Uninformed Graph-search Procedures 68 Heuristic Graph-search Procedures 72 Related Algorithms 88 ...
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 ...
We cannot depict the entire search for a solution in the figure; it is too extensive. ... regime might get stuck on local maxima, backtracking allows alternative paths to be pursued. 1.1.43. Graph Search. Graphs (or more specially, ...
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, ...
Suppose we decide to use a graph-search control regime in solving the 8-puzzle problem posed in Figure 1.1. We can keep track of the various rules applied and the databases produced by a structure called a search tree.
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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 |