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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... method can be converted to similarly faster methods for all the rest of the NP - complete problems . In the meantime , we must make do with exponential - time methods . AI researchers have worked on methods for solving several types of ...
Nils J. Nilsson. In chapters 7 and 8 , we present methods for synthesizing sequences of actions that achieve prescribed goals . These methods are illustrated by considering simple problems in robot planning and automatic program- ming ...
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 ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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