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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... heuristic information about the problem domain is used. Those rules that are “guessed,” using the heuristic information, most appropriate for that database occur early in the ordering. The applicable rules can be ordered arbitrarily if ...
... heuristic merit. 9 GO LOOP This procedure is sufficiently general to encompass a wide variety of special graph-searching algorithms. The procedure generates an explicit graph, G, called the search graph and a subset, T, of G called the ...
... -SEARCH PROCEDURES If no heuristic information from the. Fig. 2.4A search graph and search tree before expanding node 1. Fig. 2.5 A search graph and search tree after expanding. 4 O 5 2 1 6 4 8 7 5 3 into 1. 67 GRAPH-SEARCH STRATEGIES.
Nils J. Nilsson. 2.3. UNINFORMED GRAPH-SEARCH PROCEDURES If no heuristic information from the problem domain is used in ordering the nodes on OPEN, some arbitrary scheme must be used in step 8 of the algorithm. The resulting search ...
... y *28lb s :::ed ::C i|-:odu :r :::|p :ee : ::|tr |h |arc e :S : ::7A :2.:2 'g. i : F. : -: :: : :: : : : : : :|: : : : : :: : s: : : S 2.4. HEURISTIC GRAPH-SEARCH PROCEDURES The uninformed search methods, whether breadth-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 |