Posts by Collection

publications

Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning

Published in AAAI Conference on Artificial Intelligence, 2022

The contents above will be part of a list of publications, if the user clicks the link for the publication than the contents of section will be rendered as a full page, allowing you to provide more information about the paper for the reader. When publications are displayed as a single page, the contents of the above “citation” field will automatically be included below this section in a smaller font.

Recommended citation: Park, G., Choi, S., & Sung, Y. (2022, Feb). Blockwise sequential model learning for partially observable reinforcement learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 7, pp. 7941-7948).
Download Paper | Download Bibtex

Robust Imitation Learning against Variations in Environment Dynamics

Published in Proceedings of the 39 th International Conference on Machine Learning, 2022

The contents above will be part of a list of publications, if the user clicks the link for the publication than the contents of section will be rendered as a full page, allowing you to provide more information about the paper for the reader. When publications are displayed as a single page, the contents of the above “citation” field will automatically be included below this section in a smaller font.

Recommended citation: Chae, J., Han, S., Jung, W., Cho, M., Choi, S., & Sung, Y. (2022, July). Robust imitation learning against variations in environment dynamics. In International Conference on Machine Learning (pp. 2828-2852). PMLR.
Download Paper | Download Bibtex

Domain Adaptive Imitation Learning with Visual Observation

Published in 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2023

The contents above will be part of a list of publications, if the user clicks the link for the publication than the contents of section will be rendered as a full page, allowing you to provide more information about the paper for the reader. When publications are displayed as a single page, the contents of the above “citation” field will automatically be included below this section in a smaller font.

Recommended citation: Choi, S., Han, S., Kim, W., Chae, J., Jung, W., & Sung, Y. (2023). Domain adaptive imitation learning with visual observation. Advances in Neural Information Processing Systems, 36, 44067-44104.
Download Paper | Download Bibtex

Adaptive multi-model fusion learning for sparse-reward reinforcement learning

Published in Neurocomputing, 2025

The contents above will be part of a list of publications, if the user clicks the link for the publication than the contents of section will be rendered as a full page, allowing you to provide more information about the paper for the reader. When publications are displayed as a single page, the contents of the above “citation” field will automatically be included below this section in a smaller font.

Recommended citation: Park, G., Jung, W., Han, S., Choi, S., & Sung, Y. (2025). Adaptive multi-model fusion learning for sparse-reward reinforcement learning. Neurocomputing, 633, 129748.
Download Paper | Download Bibtex