Artificial Intelligence (AI) can support decision makers in managing the COVID-19 crisis across multiple dimensions. However, the question remains how to take the right actions to effectively handle an ongoing epidemic. Which are the optimal prevention strategies for infectious diseases, and how can computers automatically discover them using artificial intelligence? This is exactly the question that Pieter Libin of the Artificial Intelligence Lab has addressed in his PhD research.
His approach builds on an AI technique called Reinforcement Learning, a subfield within machine learning that learns to take the optimal decisions that lead to a desired outcome. It does so by interacting with an environment and propose strategies to reach well-specified goals in that environment.
In his research, Pieter investigated a reinforcement learning approach to automatically learn optimal prevention strategies for mitigating epidemics.