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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... reasoning steps to occur in a simple fashion in the same production system . ( Forward reasoning steps correspond to resolutions between clauses that do not descend from the theorem to be proved . ) In Figure 5.3 we show a refutation ...
... reasoning about physical events . ( McCarthy argues , for example , that people most likely do not even unconsciously - perform complex hydrodynamic simulation computations in order to decide whether or not to move in order to avoid ...
... reasoning . ( We discuss the subject of meta - knowledge below . ) Zadeh ( 1979 ) invokes the ideas of fuzzy sets to deal with problems of approx- imate reasoning . The work on default reasoning and non - monotonic logic , cited at the ...
Contents
PROLOGUE | 1 |
PRODUCTION SYSTEMS AND AI | 17 |
SEARCH STRATEGIES FOR | 53 |
Copyright | |
10 other sections not shown