17 citations · 31 across the 13 of their papers we have counts for
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cs.LG2022★ 3 cited
S2P: State-conditioned Image Synthesis for Data Augmentation in Offline Reinforcement Learning
Daesol Cho, Dongseok Shim, H. Jin Kim
Offline reinforcement learning (Offline RL) suffers from the innate distributional shift as it cannot interact with the physical environment during training. To alleviate such limi…
cs.RO2022★ 17 cited
Unsupervised Reinforcement Learning for Transferable Manipulation Skill Discovery
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. To alleviate…
cs.LG2022★ 9 cited
Automating Reinforcement Learning with Example-based Resets
Jigang Kim, J. hyeon Park, Daesol Cho +1
Deep reinforcement learning has enabled robots to learn motor skills from environmental interactions with minimal to no prior knowledge. However, existing reinforcement learning al…