no code implementations • ICLR 2022 • Sunghoon Hong, Deunsol Yoon, Kee-Eung Kim
We empirically show that the morphological information is crucial for modular reinforcement learning, substantially outperforming prior state-of-the-art methods on multi-task learning as well as transfer learning settings with different state and action space dimensions.
no code implementations • ICLR 2021 • Deunsol Yoon, Sunghoon Hong, Byung-Jun Lee, Kee-Eung Kim
Safe and reliable electricity transmission in power grids is crucial for modern society.
no code implementations • 7 Sep 2019 • Wonsup Shin, Hyolim Kang, Sunghoon Hong
In this paper, we propose a new algorithm based on the GAIL framework that includes a global encoder and the reward penalization mechanism.