This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund a $174,965 project at the College of William & Mary in Williamsburg, Virginia. The project, titled "CRII: III: REINFORCEMENT LEARNING FOR COMBINATORIAL OPTIMIZATION IN SOCIETAL PROBLEMS," aims to develop innovative artificial intelligence (AI) technologies to efficiently solve complex real-world combinatorial optimization problems (COPs) in public health and other societal domains. The key research tasks include developing graph-based reinforcement learning techniques to address challenging COPs with ill-shaped or implicit objective functions, designing robust reinforcement learning algorithms to handle uncertainty in problem parameters, and introducing a hierarchical reinforcement learning approach for multi-shot COPs. The award date is September 15, 2024, with an ultimate completion date of August 31, 2026. This interdisciplinary project seeks to promote broader participation of AI research for communities outside of AI, provide experiential learning opportunities for students, and deliver technological solutions to assist stakeholders in making more informed decisions about resource allocation and task scheduling for societal problems.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $175.0k | 6/2/24 |