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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... 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 ...
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 tree ) , algorithm A is identical to breadth - first search . We claimed earlier that the breadth - first algorithm is guaranteed to find a minimal length path to a goal . We now show that if h is a lower bound on h * ( that is ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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