Machine Learning with Constrained Resources
Abstract
This effort will research new machine learning data sets and reinforcement learning methods to address issues of statistically mismatched and incomplete information which must be annotated, collected, classified and used for rapid decisions by autonomous intelligent agent (IA) and joint IA-Human teams. In addition, multi-modal communication approaches will be investigated to ensure effective communications and understanding of intent. The goal of this research is enable joint human-intelligent agent decision making, optimizing the strengths of each in the decision process and creating an adaptive, agile team. This work applies research conducted in 61102/H48/16. In FY19, this effort was developed from realigned funds in support of the Army science and technology (S&T) priorities as identified at the December 2016 S&T Army Requirements Oversight Council by the Chief of Staff of the Army.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2019
- Source ID
- 091b13ee7443a9c88e1d0b0da88ab14c