Project Grant FA95501917032

This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research by the Texas A&M Engineering Experiment Station (Tees) to develop machine learning models for learning structural frameworks of an agent's dynamic decision-making behavior. The project aims to advance state-of-the-art methodologies for learning structural models of control by considering diverse data types, including...

This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award of $300,000 to Arizona State University (ASU) from August 2024 to July 2027 aims to enhance the performance of reinforcement learning (RL) systems in completing difficult tasks in complex environments. The project seeks to develop task and environment representations specifically for active design in RL, including: 1) Active Environment Design for RL to...

This NSF Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) Project Grant, awarded to Arizona State University in the amount of $598,123 on July 15, 2024, will develop new algorithms to enable AI systems to autonomously learn hierarchical world models and high-level actions. The goal is to create AI systems, such as hospital robots and disaster-recovery support systems, that can plan reliably and efficiently to accomplish complex user-desired tasks, without requiring...

Summary of Federal Cooperative Agreement Award Carnegie Mellon University, through its Office of Sponsored Programs Division, received a $499,287 Cooperative Agreement from the Defense Advanced Research Projects Agency (DARPA), Defense Sciences Office under the Research and Technology Development program (CFDA 12.910). The award, effective September 30, 2025 through September 29, 2027, supports research to enable embodied artificial intelligence (AI) agents to make safe and uncertainty-aware...

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 from the National Science Foundation's Computer and Information Science and Engineering program ($199,481) supports research at George Mason University from June 2023 through May 2026 to develop an approach for improving service robot decision-making and behavior during deployment in unfamiliar environments. The award aims to facilitate fast and reliable online retraining and adaptation of robot planning despite missing world knowledge. The researchers will develop a...

The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to The Ohio State University for a 3-year project from August 2024 to July 2027. The project will develop an integrated feedback real-time scheduling framework to enhance the performance and safety of autonomous driving systems (ADS). The framework will dynamically optimize the execution of ADS tasks running on embedded electronic control units...

This $700,000 Project Grant award, funded by the National Science Foundation (NSF) Division of Computer and Network Systems under the CFDA 47.070 Computer and Information Science and Engineering program, supports research to enable intelligent, real-time control and optimization of next-generation cellular wireless networks. The Texas A&M Engineering Experiment Station (Tees), a division of the Texas A&M University System, is leading this collaborative research effort. The project aims...

This EAGER (Early-concept Grants for Exploratory Research) project, funded by the National Science Foundation (NSF) Engineering program (CFDA 47.041), will advance system designs, models, and algorithms for state-aware demand control to enhance shared use of emerging autonomous mobility systems. The $150,000 award, effective May 1, 2025 through April 30, 2026, will support research at the University of California, Berkeley to address challenges in managing congestion and maximizing...

This National Science Foundation (NSF) Engineering Directorate (CFDA 47.041) Project Grant award of $397,000.00 to North Carolina State University (NC State) aims to develop an Artificial Intelligence Engineering System Analysis Assistant (AIESAA) to automate the creation of integrated transmission-distribution grid models. Key objectives include: Leveraging advanced machine learning techniques to streamline three crucial modeling tasks: scenario classification, reduced-order model selection and...