This $249,999 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports the development of a novel communication-efficient hierarchical distributed optimization framework that integrates optimization, communication, and machine learning. The core innovation is to sample and learn models of networked agents' behaviors, then use these models to predict agents' responses and enable informed decision-making while minimizing unnecessary communication and computation at the edge. The research aims to advance knowledge across three key areas - optimization, communication, and machine learning - by developing new algorithms for collaborative hierarchical optimization, integrating adaptive communication techniques with predictive models, and improving machine learning methods to account for communication and device capability uncertainties. The award will fund research activities at Louisiana State University, the prime recipient, with a project period from April 2024 to March 2027.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $250.0k | 4/3/24 |