Project Grant 2419563
Award Date
9/1/24
Completion Date
8/31/27
Dollars Obligated
$193K
Federal Agency
Division of Electrical, Communications and Cyber Systems
Federal Grant Program
47.041
Assistance Type
Project Grant
Place of Performance
Princeton, NJ 08544, USA
Similar Awards
This $193,000 federal Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) supports research on safe reinforcement learning approaches to ensure the safety of systems employing reinforcement learning in domains such as robotics, autonomous driving, and power systems. The key research thrusts include: 1) developing training policies robust to distribution shift via distributionally robust optimization, 2) enabling continual policy improvement...
The National Science Foundation (NSF) awarded a $194,000 Project Grant under the Engineering (CFDA 47.041) program to the Georgia Tech Research Corporation for a 3-year research project titled "Collaborative Research: Safe Reinforcement Learning Guaranteed by Bayesian Distributionally Robust Optimization and Online Change Point Detection." The project aims to develop new model-based reinforcement learning approaches to ensure the safety and robustness of systems employing reinforcement...
This $425,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a framework for ensuring the safety of future robotic systems. The research project, led by The Trustees of Princeton University, aims to lay the foundation for safe robot autonomy by enabling robots to continually prove the safety of their actions under a wide range of operating conditions, from complex physical...
The National Science Foundation (NSF) awarded a $375,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to the Regents of the University of Michigan, Office of Research and Sponsored Projects, doing business as the University of Michigan. The grant, awarded on October 1, 2023, aims to develop foundational technologies for safe Reinforcement Learning (RL)-enabled systems, integrating research and education. The project focuses on three key thrusts: (1)...
This National Science Foundation (NSF) Project Grant award under the Engineering program (CFDA 47.041) provides $417,239 to Arizona State University (ASU) for a 5-year project period starting September 1, 2024. The project aims to advance the fundamental algorithmic and theoretical limits of distributionally robust reinforcement learning (RL) to address the challenge of model mismatch between training and deployment environments. The research will develop provably convergent, efficient, and...
This $750,000 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program to Arizona State University focuses on developing foundational technologies for safe Reinforcement Learning (RL)-enabled systems. The 4-year project aims to establish theories, algorithms, and experiments for distributional RL to enable policy safety, exploration safety, and environmental safety in RL-powered applications like 6G networking,...
This $118,238 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research to advance reinforcement learning (RL) algorithms and frameworks. The principal investigator (PI) at the University of Texas at Austin will develop a unified, principled objective that applies to both standard and offline RL settings. This work aims to enable efficient solutions to large-scale, real-world sequential decision-making...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) Project Grant award of $375,000 will fund research to develop tools to design provably safe autonomous systems. Key activities include: Developing inverse reinforcement learning algorithms to align an RL agent's norms with those of its designers, constrained by deontic logic. Systematically exploring the agent's norms to uncover unknowns and generate surprising...
This $375,000 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), focuses on developing tools to design and verify the safety of autonomous systems. The key activities include: Developing inverse reinforcement learning algorithms to align the norms of reinforcement learning (RL) agents with human designers' intent. 2) Systematically exploring agents' norms to uncover potential safety issues. 3) Designing...
The National Science Foundation Division of Information and Intelligent Systems awarded a $545,980 Project Grant to Princeton University from August 1, 2021 through July 31, 2026 under the Computer and Information Science and Engineering program (CFDA 47.070). The grant funds research at Princeton University to develop generalization and safety guarantees for learning-based control of robots. The Computer and Information Science and Engineering program supports investigator-initiated research...