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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... nodes n , and ng be terminal nodes , and let the cost of each k - connector be k . Note that our h function provides ... leaf node of the estimated best partial solution graph to expand . Perhaps it would be efficient to select that leaf ...
... nodes at the bottom of the tree . Many of the paths end in terminal nodes at shallower levels , however , and ... leaf nodes of the search graph . The evaluation function measures the " worth " of a leaf node position . The measurement ...
... leaf node labeled by S. The result is the graph structure shown in Figure 6.3 . The two nodes labeled by S are connected by an arc that we call a match arc . Before applying a rule , an AND / OR graph , such as that of Figure 6.2 ...
PRODUCTION Systems and AI
SEARCH Strategies FOR
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