Reliable Inference in Dynamic Data Fusion
Abstract
Proper inference in a decision or inference network requires that the commander (technically: thefusion center) have an understanding of the level of trust that he / she should place in each subordinate. Recent works have addressed the problem of estimating agents’ behaviors in complex networks, of which social networks are a prominent example. These works are especially promising and would seem to be of considerable practical importance in a wide variety of command & control venues. However, these works are perhaps limited by their somewhat idealized assumptions: that the commander (fusion center) possess full information of all subordinates’ histories, and that conditional statistical independence between these histories can be assumed. In the proposed project we intend to explore more general situations: of dependent sensors, of unknown structure of that (possible) dependence, of missing data and of subordinate identities that are either obscured / adulterated / entirely missing.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 28, 2018
- Source ID
- FA95501810463
Entities
People
- Peter Willett
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Connecticut