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 search and breadth - first search . The first type of uninformed search orders the nodes on OPEN in descending order of their depth in the ... SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS 2.3. Uninformed Graph-search Procedures.
... search process generated only one successor at a time . Usually , the backtracking implementation is preferred to the depth - first ... breadth - first because expansion of nodes in the search tree proceeds along " contours " of equal ...
... SEARCH PROCEDURES x34 2117 3O4W □ 5 x 304 217 185 217 300 815 7 8 4 □ 6 Goal Node Fig . 2.7 A search tree produced by a breadth - first search . 2.4 . HEURISTIC GRAPH - SEARCH PROCEDURES The uninformed search.
Nils J. Nilsson. 2.4 . HEURISTIC GRAPH - SEARCH PROCEDURES The uninformed search methods , whether breadth - first or depth - first , are exhaustive methods for finding paths to a goal node . In principle , these methods provide a ...
... search methods , although the use of the evaluation function has resulted in substantially fewer nodes being expanded . ( If we simply use the evaluation ... breadth - first searches. 74 SEARCH STRATEGIES FOR AI PRODUCTION SYSTEMS.
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 |