Volume 97, Issue 1-2, 18-December-1997
Artificial Intelligence Vol. 97 (1-2) pp. 1-5
Copyright (c) 1997 Elsevier Science B.V. All rights reserved.
The Relevance of Relevance
Devika Subramanian, Russell Greiner, Judea Pearl
With too little information, reasoning and learning systems
cannot work effectively. Too much information can also cause the
performance of these systems to degrade, in both accuracy and efficiency.
It is therefore important to determine what information must be preserved,
or more generally, i.e., what information is "relevant".
Please reference this article as:
Devika Subramanian, Russell Greiner, Judea Pearl , The Relevance of
Relevance (Editorial), Artificial Intelligence, 97(1-2)
Preliminary version of Editorial