DocumentCode :
549185
Title :
Evaluating uncertainty representation and reasoning in HLF systems
Author :
Costa, Paulo Cesar G ; Carvalho, Rommel N. ; Laskey, Kathryn B. ; Park, Cheol Young
Author_Institution :
Center of Excellence in C4I, George Mason Univ., Fairfax, VA, USA
fYear :
2011
fDate :
5-8 July 2011
Firstpage :
1
Lastpage :
8
Abstract :
High-level fusion of hard and soft information from diverse sensor types still depends heavily on human cognition. This results in a scalability conundrum that current technologies are incapable of solving. Although there is widespread acknowledgement that an HLF framework must support automated knowledge representation and reasoning with uncertainty, there is no consensus on the most appropriate technology to satisfy this requirement. Further, the debate among proponents of the various approaches is laden with miscommunication and ill-supported assumptions, which inhibits advancement of HLF research as a whole. A clearly defined, scientifically rigorous evaluation framework is needed to help information fusion researchers assess the suitability of various approaches and tools to their applications. This paper describes requirements for such a framework and describes a use case in HLF evaluation.
Keywords :
cognition; inference mechanisms; knowledge representation; sensor fusion; uncertainty handling; HLF evaluation; HLF system; automated knowledge representation; high-level fusion; human cognition; information fusion; reasoning; uncertainty representation; Cognition; Communities; Knowledge representation; Marine vehicles; Probabilistic logic; Testing; Uncertainty; Bayesian theory; Dempster-Shafer theory; Uncertainty reasoning; evaluation framework; fuzzy theory; high-level fusion; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4577-0267-9
Type :
conf
Filename :
5977626
Link To Document :
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