Resource Constrained Deep Reinforcement Learning. - Abhinav Bhatia; Pradeep Varakantham; Akshat Kumar (ICAPS, 2019)

On the Benefits of Randomly Adjusting Anytime Weighted A. - Abhinav Bhatia; Justin Svegliato; Shlomo Zilberstein (SOCS, 2021)

Tuning the Hyperparameters of Anytime Planning: A Metareasoning Approach with Deep Reinforcement Learning. - Abhinav Bhatia; Justin Svegliato; Samer B. Nashed; Shlomo Zilberstein (ICAPS, 2022)

Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. - Samer B. Nashed; Justin Svegliato; Abhinav Bhatia; Stuart Russell 001; Shlomo Zilberstein (IROS, 2022)

Adaptive Rollout Length for Model-Based RL Using Model-Free Deep RL. - Abhinav Bhatia; Philip S. Thomas; Shlomo Zilberstein (CoRR, 2022)

RL3: Boosting Meta Reinforcement Learning via RL inside RL2. - Abhinav Bhatia; Samer B. Nashed; Shlomo Zilberstein (CoRR, 2023)