Multi-Modality Sensing and Information Fusion
Abstract
In this proposed effort, our goal is to develop novel theoretical frameworks for collaborative decision making in complex environments when the observers are both humans and physics-based sensors. Whileinformation fusion with only physics-based sensors has been a research topic for decades and has a quitemature literature, its use is restricted in certain scenarios. In particular, decision-making in complexsystems that include both human and sensor agents operating under realistic environments is becomingan important research problem with applications in military as well as in civilian such as social systems,crowdsourcing and healthcare. We will develop algorithms to perform information fusion taking human specific, and machine-specific factors as well as factors that characterize human-machine interactions intoaccount. More specifically, we will explore the factors that affect the quality of decisions made at different stages in a collaborative decision-making framework when human agents participate as decision makers. We will investigate statistical models to characterize uncertainties, cognitive limitations and otherhuman-related factors and use these statistical models to investigate the impact of such uncertaintieson overall fusion performance.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2017
- Source ID
- FA95501710313
Entities
People
- Pramod Varshney
Organizations
- Air Force Office of Scientific Research
- Syracuse University
- United States Air Force