Fusion 2016 Special Session on
Evaluation of Technologies for Uncertainty Reasoning
Table of Contents:
- Description of the Special Session
- Research Topics that will Develop
- List of Papers/Presentations
Paulo Costa George Mason University, Fairfax, VA, USA
Kathryn Laskey George Mason University, Fairfax, VA, USA
Anne-Laure Jousselme NATO CMRE, La Spezia, Italy
Erik Blasch AFRL, Rome, NY, USA
Jüergen Ziegler IABG, Ottobrunn, Germany
Valentina Dragos ONERA, France
Pieter DeVilliers University of Pretoria, Pretoria, South Africa
Gregor Pavlin D-CIS Lab, Thales R&T, Delft, The Netherlands
The ETUR Session is intended to report the latest results of the ISIF’s ETURWG, which aims to bring together advances and developments in the area of evaluation of uncertainty representation. The ETURWG special sessions started in Fusion 2010 and has been held ever since, which an attendance consistently averaging between 40 and 48 attendees. While most attendees consist of ETURWG participants new researchers and practitioners interested in uncertainty evaluation have attended the sessions and some stayed with the ETURWG.
The session will focus three topics:
(1) to summarize the state of the art in uncertainty analysis, representation, and evaluation,
(2) discussion of metrics for uncertainty representation, and
(3) survey uncertainty at all levels of fusion.
The impact to the ISIF community would be an organized session with a series of methods in uncertainty representation as coordinated with evaluation. The techniques discussed and questions/answers would be important for the researchers in the ISIF community; however, the bigger impact would be for the customers of information fusion systems to determine how measure, evaluate, and approve systems that assess the situation beyond Level 1 fusion.
The customers of information fusion products would have some guidelines to draft requirements documentation, the gain of fusion systems over current techniques, as well as issues that important in information fusion systems designs. One of the main goals of information fusion is uncertainty reduction, which is dependent on the representation chosen. Uncertainty representation differs across the various levels of Information Fusion (as defined by the JDL/DFIG models). Given the advances in information fusion systems, there is a need to determine how to represent and evaluate situational (Level 2 Fusion), impact (Level 3 Fusion) and process refinement (Level 5 Fusion), which is not well standardized for the information fusion community.
The complete list of papers and presentations will be posted here once the session and the posters were approved.