This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award provides $108,647 to Yale University to develop a novel algorithmic framework for solving computational and statistical problems, with applications in modern artificial intelligence and machine learning systems. The framework, called the "LCP Scheme" (Lift, Conserve, and Project), leverages Hamiltonian dynamics to design more efficient and...
The National Science Foundation (NSF) has awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CISE) program to The Trustees of Columbia University in the City of New York, operating through its Sponsored Projects Administration Division. The 3-year grant, awarded on February 1, 2024, supports research to address open questions in algorithmic game theory and its applications to online markets and platforms. Key research objectives include developing new...
This $600,000 National Science Foundation project grant supports research at Stony Brook University to develop a suite of novel distributed reinforcement learning algorithms. The grant is funded through the NSF's Computer and Information Science and Engineering program.
Specifically, the three-year award will fund research to establish theoretical foundations for designing, analyzing, and applying fully distributed reinforcement learning algorithms over large-scale networks without global...
The National Science Foundation (NSF) awarded a Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the Massachusetts Institute of Technology (MIT) in the amount of $227,984. The award, titled "CAREER: Pushing the Boundaries of Learning Dynamics and Equilibrium Computation in Games: Control, Complexity, and Nonlinear Optimization," aims to advance the theoretical and practical understanding of equilibrium computation,...
The National Science Foundation awarded a $499,962 Project Grant to Stanford University from June 2021 through May 2024 under the Computer and Information Science and Engineering program (CFDA 47.070).
The grant will support research into algorithmic game theory, equilibria, and related topics. As part of the Computer and Information Science and Engineering program's goals around advancing computing and communications research and infrastructure, this project aims to advance the development...
This Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems supports research to significantly increase the scalability of algorithms for solving large-scale, multi-step, imperfect-information strategic interactions. Specifically, the $854,896 award to Carnegie Mellon University (CMU) from August 1, 2023 to July 31, 2026 will fund the design, implementation, and testing of novel techniques in three main areas:
Scalable subtree solving...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) project grant, awarded under CFDA 47.070, will develop game-theoretic algorithms to enable safe and efficient interaction between autonomous agents and humans, even in partially observable environments with uncertainty. The $237,999 award to the University of Colorado will focus on three phases: cooperative agents with shared goals, zero-sum agents with opposing goals, and general-sum agents with...
The National Science Foundation awarded $175,000 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) to the Regents of the University of Michigan for a two-year project grant titled "Analysis and Applications of Multi-Level Games." The project aims to advance empirical game-theoretic analysis methodology to incorporate features of underlying game tree models into empirical game models. Specifically, the university researchers will adapt...
This Project Grant from the National Science Foundation Division of Information and Intelligent Systems provides $398,958 in funding to The Washington University from January 1, 2023 to December 31, 2025. The grant supports research and curriculum development activities aligned with the Computer and Information Science and Engineering federal grant program.
Specifically, the grant will advance the use of deep learning and gradient-based optimization methods to develop new computational tools...
This Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) provides $425,225 to the University of Maryland, College Park to conduct research on the foundations of dynamic multi-agent learning under information constraints. The key research thrusts of this 5-year award include: 1) formally introducing the concept of "information structure" from decentralized stochastic control into the theoretical studies of dynamic multi-agent learning, 2)...