13 citations · 14 across the 3 of their papers we have counts for
3 papers
RL: Boosting Meta Reinforcement Learning via RL inside RL
Abhinav Bhatia, Samer B. Nashed, Shlomo Zilberstein
Meta reinforcement learning (Meta-RL) methods such as RL have emerged as promising approaches for learning data-efficient RL algorithms tailored to a given task distribution. H…
Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL
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 int…
Resource Constrained Deep Reinforcement Learning
Abhinav Bhatia, Pradeep Varakantham, Akshat Kumar
In urban environments, supply resources have to be constantly matched to the "right" locations (where customer demand is present) so as to improve quality of life. For instance, am…