Reinforcement Learning (RL) is a Machine Learning (ML) paradigm, used for decision-making tasks, where an agent learns to achieve a specified goal, by interacting with its underlying environment. Compared to the widely explored games and physics simulation problems in RL, real-world RL systems must contend with much more technical challenges. We explore the use of RL in healthcare applications.
RL4H
Reinforcement Learning for Health
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- GluCoEnv Public
GluCoEnv - Glucose Control Environment, is a simulation environment which aims to facilitate the development of Reinforcement Learning based Artificial Pancreas Systems for Glucose Control in Type 1 Diabetes.
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