Project Grant 2448885
- This Project Grant award, valued at $200,000.00 and awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop a scalable framework for achieving robust and assured performance of autonomous agents, such as warehouse robots, delivery robots, drones, and robo-taxis, in real-world environments. The research will integrate formal methods, reinforcement learning, and multi-agent control theory to address critical...
- 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...
- This $1,200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of novel algorithms and computational frameworks to enable safe and reliable deployment of AI-driven autonomous systems. The project at the University of Southern California (USC) aims to design algorithms that use representation learning to summarize high-dimensional sensor data, such as from cameras and LiDAR, into compact...
- This $120,000 Project Grant was awarded on July 1, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Regents of the University of California at Riverside (UC Riverside). The funding will support a collaborative research project focused on enhancing the safety and reliability of autonomous driving systems through the development of advanced detection and countermeasure techniques at the application, system, and...
- This $272,238 Project Grant, awarded on July 15, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enhance the safety and reliability of autonomous vehicles. The project aims to identify vulnerabilities in the software and machine learning components of autonomous vehicle systems, and develop mitigation techniques to improve their overall resilience. The research will combine model-based and...
- This $300,000 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will fund research by the Regents of the University of California at Riverside (UC Riverside) to develop trustworthy and resilient coordination mechanisms for multi-agent systems. The project aims to enable autonomous systems like drones, vehicles, robots, and smart infrastructure to reliably work together, even when facing uncertainty, failure, or...
- This $519,563 federal Project Grant awarded by the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will fund research to develop new mathematical tools and algorithms that enable large groups of autonomous agents, such as drones and ground robots, to operate safely, efficiently, and collaboratively. The central focus is on modeling these multi-agent systems as evolving spatial distributions rather than individually, enabling the design of scalable and practical algorithms...
- 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...
- The National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program awarded a $600,000 Project Grant to the University of California, Berkeley (UC Berkeley) to develop new techniques for autonomous systems to learn effective behaviors while always respecting strict safety constraints. The 3-year project (1/1/2026 - 12/31/2028) will tackle a core challenge in making intelligent machines like self-driving cars and delivery robots reliable and trustworthy by...
- This $439,425 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research to enable the safe deployment of learning-enabled systems that can robustly learn and optimize their behavior based on uncertain human feedback and intent. The key objectives are to: (1) develop methods for providing probabilistic performance guarantees when learning policies from human input,...
This $400,000 Project Grant was awarded on August 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The grant is funding collaborative research by the University of Southern California (USC) to develop a scalable framework for high-assurance design of safety-critical and mission-critical cooperative autonomous agents, such as warehouse robots, delivery robots, drones, and self-driving vehicles. The research aims to address challenges in ensuring robust real-world performance of these autonomous agents by incorporating methods for runtime monitoring, adaptation, and adherence to operational rules and safety constraints. The project will leverage formal methods, reinforcement learning, and multi-agent control theory to enhance the reliability and resilience of these AI-driven autonomous systems with potential applications in transportation, robotics, and smart manufacturing.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $400.0k | 7/31/25 |