Project Grant 2546185
- This $450,000 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop novel specification-guided multi-agent reinforcement learning approaches for constructing more scalable, interpretable, and safer multi-agent systems. The project, led by Northeastern University, has three key research objectives: (A) developing methods to optimally decompose formal specifications and assign them to...
- This $749,963 Project Grant was awarded by the National Science Foundation (NSF) Division of Computing and Communication Foundations on October 1, 2023. The grant is funded under the NSF's Computer and Information Science and Engineering (CFDA #47.070) program, which supports investigator-initiated research and education across all areas of computing, communications, and information science and engineering. The grant was awarded to Northeastern University, a private, non-profit research...
- This $1,500,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports the University of Southern California's research on safe multi-agent systems using a neurosymbolic approach. The project aims to develop new theories and algorithms for the design of safe learning-enabled multi-agent systems, with applications in areas like wildfire prevention using drone swarms and semi-automated...
- The National Science Foundation (NSF) awarded a $538,000 Project Grant under the Engineering program (CFDA 47.041) to the University of Maryland, College Park. The grant, titled "CAREER: Foundations of Dynamic Multi-Agent Learning Under Information Constraints", aims to bridge insights from control theory and machine learning to advance the theoretical foundations for dynamic multi-agent learning in partially observable environments. The key research thrusts include: 1) formally...
- This Project Grant award of $299,664 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research to explore how reinforcement learning (RL) agents can effectively learn to both cooperate and compete with each other in complex, many-agent environments. The project aims to develop techniques from statistical mechanics, control theory, and management sciences to enable RL agents to model and anticipate the actions of...
- The National Science Foundation (NSF) awarded a $398,990 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of California, Irvine (UCI). The grant, awarded on August 1, 2025, supports a research project that explores fundamental principles underlying how groups of intelligent agents interact and learn within shared environments. The project aims to develop a robust theoretical framework for analyzing learning processes in multi-agent...
- This Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) provides $356,488 to the Texas A&M Engineering Experiment Station (Tees) to develop a resilient reinforcement learning (RL) framework for managing heterogeneous multi-agent systems in complex and structured environments. The research aims to produce scalable and computationally-efficient RL algorithms with rigorous convergence and complexity analysis for applications like interference management...
- This Project Grant award of $300,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support collaborative research to develop trustworthy and resilient coordination mechanisms for multi-agent systems (CFDA 47.070). The project aims to revolutionize multi-agent systems (MAS) by creating intelligent coordination algorithms capable of maintaining performance and safety, even in the presence of uncertainty, failure, or conflict....
- The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $400,000 Project Grant to The Trustees of Princeton University, Office of Research and Project Administration, under the NSF Computer and Information Science and Engineering (CFDA 47.070) program. This 3-year grant supports collaborative research on developing theories and algorithms for scalable multi-agent planning and control to enable safe and robust autonomous electrical vertical take-off and...
- The National Science Foundation awarded a $499,835 Project Grant to George Washington University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the period of October 1, 2021 through September 30, 2024. The grant funds research titled "SMALL: HIGH-PERFORMANCE MULTI-AGENT REINFORCEMENT LEARNING" which will advance the development of multi-agent reinforcement learning techniques. As described under the CFDA program, the NSF aims to...
This $450,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA #47.070) program supports a collaborative research project titled "COLLABORATIVE RESEARCH: FMITF: TRACK I: SPECIFICATION-GUIDED MULTIAGENT REINFORCEMENT LEARNING". The project aims to develop novel approaches that combine formal methods and multi-agent reinforcement learning to construct more scalable, interpretable, and safer multi-agent systems for applications such as robotics, computer networks, and power grids. The key research objectives include developing specification-guided multi-agent reinforcement learning methods, analyzing emergent coordinated behaviors in multi-agent systems, and disseminating the research findings through education and training of graduate and undergraduate students. The award was made to Villanova University, a private research university with a long history of federal research and educational contracts and grants across scientific and technological domains.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $450.0k | 8/29/25 |