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
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... first attempting to move the blank square left, then up, then right, then ... depth bound of this backtracking process. In Figure 1.3 we show a sequence ... search for a solution in the figure; it is too extensive. Eventually though, a ...
... depth-first graph-search) control strategies should be used when there are multiple paths between problem states because these strategies tend to avoid exploring all of the paths. 1.9 In using a backtracking strategy with procedure ...
... FIRST(RULES); the best of the applicable rules is selected. 6 RULES - TAIL ... First, it terminates successfully (in step 1) only if it produces a database ... depth exceeds this bound. 56 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS.
... search procedure is called uninformed. In AI, we are typically not interested in uninformed procedures, but we describe two types here for purposes of comparison: depth-first search and breadth-first search. The first type of uninformed ...
... depth-first version of GRAPHSEARCH because backtracking is simpler to implement and involves less storage. (Backtracking strategies save only one path to a goal node; they do not save the entire record of the search as do depth-first ...
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 |