no code implementations • 29 Aug 2023 • Jigang Kim, Dohyun Jang, H. Jin Kim
Deploying multiple robots for target search and tracking has many practical applications, yet the challenge of planning over unknown or partially known targets remains difficult to address.
1 code implementation • 17 May 2023 • Jigang Kim, Daesol Cho, H. Jin Kim
While reinforcement learning (RL) has achieved great success in acquiring complex skills solely from environmental interactions, it assumes that resets to the initial state are readily available at the end of each episode.
1 code implementation • 11 Oct 2022 • Seungjae Lee, Jigang Kim, Inkyu Jang, H. Jin Kim
Hierarchical Reinforcement Learning (HRL) has made notable progress in complex control tasks by leveraging temporal abstraction.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 29 Apr 2022 • Daesol Cho, Jigang Kim, H. Jin Kim
Current reinforcement learning (RL) in robotics often experiences difficulty in generalizing to new downstream tasks due to the innate task-specific training paradigm.
1 code implementation • 5 Apr 2022 • Jigang Kim, J. Hyeon Park, Daesol Cho, H. Jin Kim
Deep reinforcement learning has enabled robots to learn motor skills from environmental interactions with minimal to no prior knowledge.