1 code implementation • 28 Jun 2023 • Abhinav Bhatia, Samer B. Nashed, Shlomo Zilberstein
Meta reinforcement learning (meta-RL) methods such as RL$^2$ have emerged as promising approaches for learning data-efficient RL algorithms tailored to a given task distribution.
no code implementations • 6 Jun 2022 • Abhinav Bhatia, Philip S. Thomas, Shlomo Zilberstein
Model-based reinforcement learning promises to learn an optimal policy from fewer interactions with the environment compared to model-free reinforcement learning by learning an intermediate model of the environment in order to predict future interactions.
no code implementations • 3 Dec 2018 • Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
However, existing Deep RL methods are unable to handle combinatorial action spaces and constraints on allocation of resources.