This Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems, under the NSF CISE (Computer and Information Science and Engineering) program (CFDA 47.070), provides $424,916 to the Board of Regents of the University of Nebraska (dba University of Nebraska) from August 1, 2023 to July 31, 2027. The award supports collaborative research to investigate decision-making frameworks for open multiagent systems, where agents may enter/leave the...
This National Science Foundation (NSF) Division of Information and Intelligent Systems Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $299,214 over 4 years to Oberlin College to conduct collaborative research on decision-making methods for open multi-agent systems. The research investigates how autonomous agents can make optimal decisions under various types of uncertainty, including changes to the system composition, tasks,...
This $398,990 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research exploring fundamental principles underlying multi-agent learning and interactions in complex systems. The primary goals are to develop computationally efficient algorithms that provably converge to equilibrium states, particularly in scenarios with both cooperative and competitive agent interactions and large action...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program provides $948,000 in funding to the Georgia Tech Research Corp to develop new methods for data-efficient decision-focused learning. The research aims to create a general framework for tailoring predictive models to address uncertainty factors and integrate them into decision-making problems across domains such as public health, environmental...
This $279,399 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support the development of novel techniques and methods to adapt foundation models for multimodal sequential decision-making. The project aims to significantly increase the applicability of foundation models across a wide range of sequential decision-making applications, such as smart manufacturing, multi-agent systems, and...
This National Science Foundation project grant award of $664,846 provides funding from July 1, 2022 to June 30, 2025 to support research at the University of South Carolina under the Computer and Information Science and Engineering program (CFDA 47.070). The award will support the development of novel methods for scalable and learnable multi-agent commitments to facilitate cooperative artificial intelligence planning and learning. The research consists of two thrusts. The first will redesign...
This Project Grant award of $160,673 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to combine algorithms and machine learning to improve decision-making under uncertainty. The project, led by New York University (NYU), will explore incorporating machine-learned predictions into algorithm design as well as developing learning models optimized for specific algorithmic objectives. This work aims to create a...
This Project Grant award of $101,476 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop reliable machine learning algorithms for decision-making in complex feedback systems. The award, running from April 1, 2025 to March 31, 2030, will fund research on leveraging potentially unreliable machine learning predictions while ensuring safety and performance, learning long-term impact models from non-stationary...
This National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CFDA 47.070) program aims to develop software frameworks that can efficiently serve and deploy machine learning models for a variety of AI-powered applications. The $600,000 award, spanning from October 2024 to September 2027, tasks the prime awardee, Georgia Tech Research Corporation, with creating agile mechanisms and policies to serve a family of AI models across...
This $438,342 Project Grant awarded by the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research to develop efficient and rigorous techniques for solving complex, multi-objective decision-making problems under uncertainty. The research aims to facilitate tradeoffs among multiple objectives while using statistically valid algorithms to achieve high efficiency. Key approaches include novel comparison techniques, data recycling, computer simulation, and parallel...