no code implementations • 2 Nov 2022 • Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui
The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation.
1 code implementation • 26 Sep 2022 • Desik Rengarajan, Sapana Chaudhary, Jaewon Kim, Dileep Kalathil, Srinivas Shakkottai
Meta reinforcement learning (Meta-RL) is an approach wherein the experience gained from solving a variety of tasks is distilled into a meta-policy.
1 code implementation • 6 Mar 2022 • Rayan El Helou, Kiyeob Lee, Dongqi Wu, Le Xie, Srinivas Shakkottai, Vijay Subramanian
This paper presents OpenGridGym, an open-source Python-based package that allows for seamless integration of distribution market simulation with state-of-the-art artificial intelligence (AI) decision-making algorithms.
1 code implementation • ICLR 2022 • Desik Rengarajan, Gargi Vaidya, Akshay Sarvesh, Dileep Kalathil, Srinivas Shakkottai
We demonstrate the superior performance of our algorithm over state-of-the-art approaches on a number of benchmark environments with sparse rewards and censored state.
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.
1 code implementation • NeurIPS 2021 • Khaled Nakhleh, Santosh Ganji, Ping-Chun Hsieh, I-Hong Hou, Srinivas Shakkottai
This paper proposes NeurWIN, a neural Whittle index network that seeks to learn the Whittle indices for any restless bandits by leveraging mathematical properties of the Whittle indices.
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.
no code implementations • 21 Jun 2020 • Kiyeob Lee, Desik Rengarajan, Dileep Kalathil, Srinivas Shakkottai
We introduce a natural refinement to the equilibrium concept that we call Trembling-Hand-Perfect MFE (T-MFE), which allows agents to employ a measure of randomization while accounting for the impact of such randomization on their payoffs.
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.