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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... problems of interest in AI , however , the most natural formulations involve noncommutative systems . Typical problems of this sort are ones where goals are achieved by a sequence ( or program ) of actions . Robot problem solving and ...
... solve problems that the other cannot . In fact , by suitable control mechanisms , the problem - solving traces of different types of systems can be made essentially identical . The point is that to solve robot problems efficiently with ...
... problem - solving system is described in Fikes and Nilsson ( 1971 ) . The version of STRIPS discussed in this ... solving more difficult problems . Triangle tables play a key role in this process . The GPS system was developed by Newell ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
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