DOPE: Doubly Optimistic and Pessimistic Exploration for Safe Reinforcement Learning

1 code implementation • 1 Dec 2021 • Archana Bura, Aria HasanzadeZonuzy, Dileep Kalathil, Srinivas Shakkottai, Jean-Francois Chamberland

Safe reinforcement learning is extremely challenging--not only must the agent explore an unknown environment, it must do so while ensuring no safety constraint violations.

reinforcement-learning Reinforcement Learning (RL) +2

Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs

no code implementations • 1 Aug 2020 • Aria HasanzadeZonuzy, Archana Bura, Dileep Kalathil, Srinivas Shakkottai

Many physical systems have underlying safety considerations that require that the policy employed ensures the satisfaction of a set of constraints.

reinforcement-learning Reinforcement Learning (RL)

QFlow: A Learning Approach to High QoE Video Streaming at the Wireless Edge

no code implementations • 4 Jan 2019 • Rajarshi Bhattacharyya, Archana Bura, Desik Rengarajan, Mason Rumuly, Bainan Xia, Srinivas Shakkottai, Dileep Kalathil, Ricky K. P. Mok, Amogh Dhamdhere

The predominant use of wireless access networks is for media streaming applications, which are only gaining popularity as ever more devices become available for this purpose.