Principles of Artificial Intelligence
A 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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... assertions for each relation not affected by an action . For example , we need the following assertion to express ... assertions , describing what stays the same during an action , are sometimes called the frame assertions . In large ...
... assertions . Any reasonable theorem - proving method might be used . As already mentioned , Green used a resolution ... assertions describing the initial state might be used as facts , and the action and frame assertions might be used as ...
... assertions 1-11 as facts and use assertions 12-14 as rules . The details of operation of such a system would depend on whether the rules were used in a forward or backward manner and on the specific control strategy used by the system ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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