Reinforcement Learning based Recommender Systems

We present a Reinforcement Learning (RL) based approach to implement Recommender Systems. The results are based on a real-life Wellness app that is able to provide personalized health/ activity related content to users in an interactive fashion. Unfortunately, current recommender systems are unable to adapt to continuously evolving features. To overcome this, we propose three constructs, which we believe are essential for RL to be used in Recommender Systems.

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