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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... applications and the resulting global databases by an interest- ing structure called a derivation graph . A ... rule . It is obvious , of course , that the two structures of Figure 3.4 and Figure 3.6 are identical except for arc ...
... rule applied to a derivation graph can be regarded as producing a new derivation graph . The rule application adds one new node to the structure . Thus , rule RI ' adds the node labeled T in Figure 3.6 . We can define the cost of the ...
... rule , the CONSE structure ( regarded as a fact ) must match the goal structure . Then , the ANTE structure ( appropriately instantiated ) is the subgoal produced by the rule application . Again , the situation is more complex ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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