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 Intelligence"evolved 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 REPRESENTATION Efficient problem solution requires more
than an efficient control strategy . It requires selecting good representations for
problem states , moves , and goal conditions . The representation of a problem
has a ...
The computational effort is the same for both directions . There are occasions ,
however , when it is more efficient to solve a problem in one direction rather than
the other . Suppose , for example , that there were a large number of explicit goal
Of course , merely because one algorithm expands fewer nodes than another
does not imply that it is more efficient . The more informed algorithm may indeed
have to make more costly computations , which would destroy efficiency .
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