Artificial Intelligence

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)   (1997) 1-5.

Preliminary version of Editorial (pdf)  (ps)