Using Reinforcement Learning for Operating Educational Campuses Safely during a Pandemic (Student Abstract)
Keywords:Applications Of AI, Reinforcement Learning, Education, Pandemic Control
AbstractThe COVID-19 pandemic has brought a significant disruption not only on how schools operate but also affected student sentiments on learning and adoption to different learning strategies. We propose CampusPandemicPlanR, a reinforcement learning-based simulation tool that could be applied to suggest to campus operators how many students from each course to allow on a campus classroom each week. The tool aims to strike a balance between the conflicting goals of keeping students from getting infected, on one hand, and allowing more students to come into campus to allow them to benefit from in-person classes, on the other. Our preliminary results show that reinforcement learning is able to learn better policies over iterations, and that different Pareto-optimal tradeoffs between these conflicting goals could be obtained by varying the reward weight parameter.
How to Cite
Ondula, E. A., & Krishnamachari, B. (2022). Using Reinforcement Learning for Operating Educational Campuses Safely during a Pandemic (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 13025-13026. https://doi.org/10.1609/aaai.v36i11.21649
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