Uncertain Information Fusion and Knowledge Integration: How to Take Reliability into Account

Authors

Hung T. Nguyen, New Mexico State University - Main CampusFollow
Kittawit Autchariyapanitkul, Maejo UniversityFollow
Olga Kosheleva, The University of Texas at El PasoFollow
Vladik Kreinovich, The University of Texas at El PasoFollow

Publication Date

4-2017

Comments

Technical Report: UTEP-CS-17-02a

To appear in Proceedings of the Joint 17th Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, Otsu, Japan, June 27-30, 2017.

Abstract

In many practical situations, we need to fuse and integrate information and knowledge from different sources -- and do it under uncertainty. Most existing methods for information fusion and knowledge integration take into account uncertainty. In addition to uncertainty, we also face the problem of reliability: sensors may malfunction, experts can be wrong, etc. In this paper, we show how to take into account both uncertainty and reliability in information fusion and knowledge integration. We show this on the examples of probabilistic and fuzzy uncertainty.