Advancing Human-Machine Symbiosis Using Hybrid Methods for Collaborative Problem-Solving
Abstract
The Center for Multisource Information Fusion (CMIF) at the University at Buffalo, with Lockheed’s Advanced Technology Laboratories (ATL), is proposing research and design of a unique symbiotic Human-Computer analysis capability that addresses what may be the most distinctive intelligence/ISR analysis technology shortfall for synthesizing situational and threat understanding. In the face of complex modern operational problems, analysts are being provided Analysis Tool Suites (ATS’s) that offer individually helpful but disparate toolkit systems that still leave the “story” assembly as a high cognitive workload activity. Based on existing research and assessments at both CMIF and ATL—on a major Army grant and on an IRAD project—we are proposing to leverage that work in a proposed design effort for a hybrid Human-Computer based capability grounded in: 1) argumentation principles, 2) story/causal methods, 3) anytime decision-making, and 4) the Transferable Belief Model (TBM) to provide marked reduction in the analyst cognitive workload but also yielding more holistic analyses. The combination of these methods accommodates the Open-World requirement of “Unknown Unknowns”, provides embedded explanation features, balances pro and contra aspects of evidential reasoning, and addresses uncertainty and information pedigree. These methods have public utility in Law, Teaching of Critical Thinking, Medical Diagnosis, and Criminal Analysis.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 09, 2016
- Source ID
- N002441510051
Entities
People
- James Llinas
Organizations
- Research Foundation for the State University of New York
- United States Air Force