CAREER: Assured Reinforcement Learning from Human Feedback for Cyber-Physical Systems — NSF Award to University of Florida (FL, $6
This CAREER project will develop new methods that allow cyber-physical systems, such as robotaxis, service robots, and autonomous drones, to adapt to individual human preferences using simple feedback. Today, many such systems rely on fixed rules designed in advance, which makes it difficult for them to respond to diff
| Award title | CAREER: Assured Reinforcement Learning from Human Feedback for Cyber-Physical Systems |
|---|---|
| Award ID | 2541603 |
| Awardee | University of Florida |
| City | GAINESVILLE |
| State | FL |
| Amount obligated | $659,317 |
| Principal investigator | Yu Wang |
| Program | CPS-Cyber-Physical Systems |
| Start date | 06/01/2026 |
| Abstract | This CAREER project will develop new methods that allow cyber-physical systems, such as robotaxis, service robots, and autonomous drones, to adapt to individual human preferences using simple feedback. Today, many such systems rely on fixed rules designed in advance, which makes it difficult for them to respond to differences in how people prefer to work or interact with them. This project will enable these systems to learn from intuitive input that non-expert users can provide, such as choosing |
| Source | NSF Awards |
$799/mo
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