This $375,000 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The goal of the project is to develop tools and methods to help ensure the safe operation of autonomous systems that utilize reinforcement learning (RL) algorithms. Key activities include: 1) developing inverse RL algorithms to learn an agent's reward function from demonstrations, 2) exploring the agent's norms to...
This federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $375,000 to the University of Massachusetts to conduct research on aligning the norms of autonomous robots with human values. The key activities include: Developing inverse reinforcement learning algorithms to learn reward functions from demonstrations constrained by deontic logic. Systematically exploring the trained agent's...
This Project Grant award, valued at $375,000 and awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports The Ohio State University's research on safe and reliable reinforcement learning (RL) systems. The key objectives of this 4-year project are to develop foundational technologies for safe RL-enabled systems, including policy safety, exploration safety, and environmental safety. The research will...
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 $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 $194,000 Project Grant under the Engineering program (CFDA 47.041) to Georgia Tech Research Corp to conduct research on safe reinforcement learning. The project aims to develop new approaches for training, improving, and evaluating reinforcement learning policies that are robust to distribution shift and non-stationarity, with the goal of ensuring safety in applications such as robotics, autonomous driving, and power systems. Key innovations...
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 $128,238 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research at the University of Texas at Austin to advance reinforcement learning (RL) through the development of a unified, principled off-policy algorithm framework. The research aims to enable more efficient, large-scale real-world sequential decision-making applications such as self-driving cars, industry automation, and natural...
This federal Project Grant award of $800,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) is supporting research to develop methods for certifying the safety of autonomous systems that use deep learning-enabled perception, prediction, and control components. The key goals of the project are: (1) to develop techniques for learning safety certificates and control policies for these types of learning-enabled autonomous...
This Project Grant award, valued at $569,138, was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The award supports the development of new methods for actively testing autonomous decision-making systems that utilize reinforcement learning (RL) algorithms. The key objectives are to derive optimal policies for evaluating RL-based autonomous systems, create novel adaptive sampling algorithms to improve policy...