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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... structure of a complex organic compound , given certain experimental data such as a mass spectrogram of a sample of ... structure : Initially , the database describes no chemical structure and contains merely the chemical formula ; at ...
... structure to match a fact network structure , the formula associated with the goal structure must unify with some sub - conjunction of the formulas associated with the fact structure . In these examples , we merely have to find fact ...
... structure is first broken into component structures , and when these are matched individually by rule CONSE structures . As a more complex example we show , in Figure 9.27 , the network version of an implication used earlier : EQ [ y ...
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