| Article ID: | iaor20011113 |
| Country: | Canada |
| Volume: | 38 |
| Issue: | 3 |
| Start Page Number: | 132 |
| End Page Number: | 144 |
| Publication Date: | Aug 2000 |
| Journal: | INFOR |
| Authors: | Pawlak Zdzislaw |
| Keywords: | artificial intelligence: decision support, decision theory |
Rough set theory is a new mathematical approach to vagueness and uncertainty. The theory has found many real life applications world wide. It is also considered as a very well suited new mathematical tool to deal with various decision problems and many papers on rough set theory and decision support have been published recently. Rough set theory gives new insight into the decision process and offers new efficient algorithms. Several real life decision problems have been successfully solved using this approach. In this paper basic concepts of rough set theory will be given and its significance for decision analysis will be briefly discussed.