Using Probabilistic Planning to Model the Spread of COVID-19 in Kingston, Ontario (Student Abstract)

Abstract

This work leverages probabilistic planning to both generate a geographical agent-based model of COVID-19 in Kingston, Ontario, and to facilitate policy creation via JaxPlanner with the aim of optimally implementing mask and vaccine mandates on a population. Ultimately, the aforementioned policies were successful at minimizing burden on the simulated population.

Publication
Canadian Conference on Electrical and Computer Engineering (CCECE): Student Poster
Date
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