Project Grant 2314182
Award Date 9/1/23
Completion Date 8/31/27
Dollars Obligated $817K
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Boston, MA 02115, USA
Similar Awards
- This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program, totaling $209,267, will fund research to close the simulation-to-reality (sim-to-real) gap in reinforcement learning (RL). The research will develop new techniques using randomization, alignment, and derivation mechanisms to improve the applicability and generalization of RL systems from simulated to real-world environments. The goal is to...
- This federal Project Grant award of $476,440 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a performance period of September 1, 2025 through August 31, 2030, supports research to develop new algorithms for unsupervised and autonomous reinforcement learning of skills. The key objectives of this project are to: 1) develop algorithms that can discover reusable skills through trial-and-error learning, without requiring human...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $472,934 to Northeastern University to address a critical challenge in artificial intelligence (AI) - how to make machine learning more efficient in real-world scientific and engineering settings where data is sparse or imperfect. The research program focuses on incorporating symmetry, an organizing principle in nature, into...
- This $398,856 National Science Foundation project grant supports research at Northwestern University to improve reinforcement learning algorithms. Specifically, the grant funds the development of sample-efficient and computationally-efficient algorithms for both online and offline reinforcement learning with function approximation. The researchers aim to incorporate optimistic exploration and pessimistic exploitation techniques using faithful uncertainty quantification for neural networks....
- 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...
- This Project Grant award from the National Science Foundation (CFDA 47.070 - Computer and Information Science and Engineering) provides $124,998 to Worcester Polytechnic Institute (WPI) to advance robotic manipulation capabilities in unstructured real-world environments. The research aims to enable robots to autonomously learn abstract representations of states and actions from sensory and execution data, enhancing their ability to plan and execute complex tasks. The project intends to...
- This NSF CISE program Project Grant award of $544,114 to New York University (NYU) is funding research on "NUMERICALLY EFFICIENT REINFORCEMENT LEARNING FOR CONSTRAINED SYSTEMS WITH SUPER-LINEAR CONVERGENCE (NERL)". The project aims to develop new reinforcement learning algorithms that can more efficiently create behaviors for real-world robotic applications, while ensuring operational safety. The research will explore ways to improve learning efficacy and guarantee safety, and will...
- This $299,999 Project Grant awarded by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to enhance the performance of reinforcement learning (RL) systems in completing complex tasks in challenging environments. The project aims to develop new task and environment representations to enable active learning strategies that optimize resource allocation and reduce the need for extensive physical interactions with the...
- 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 five-year, $205,073 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support research at Tufts University to develop methods for transferring multisensory object knowledge across collaborative robots. The Principal Investigator will work to enable robots with different bodies, sensors and movement capabilities to learn from each other's experiences manipulating and perceiving objects through various senses. This...