# Federated Reinforcement Learning: From Heterogeneous Environments to Offline Data

**Budget Signal Score:** 40/100

| Field | Value |
|---|---|
| Institution | Auburn University |
| Location | AUBURN, AL |
| Project | Federated Reinforcement Learning: From Heterogeneous Environments to Offline Data |
| Award amount | $299,970 |
| Obligated so far | $299,970 |
| Awarded | 2026-08-04 |
| Period | 2026-10-01 to 2029-09-30 |
| Program | CSCS: Circuits and Systems for |
| Directorate / division | ENG / ECCS |
| Award ID | 2545289 |

## Why this score
- Award of $299,970.
- Equipment- and compute-heavy field.

Source: U.S. National Science Foundation Awards API (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2545289). Last refreshed: 2026-11-04T18:13:44.963Z.
Award data comes from the NSF Awards API and may be amended by NSF. Institution-level only; investigator contact details are not included. Informational only.