@inproceedings{yoon2025enhancing,title={Enhancing Naphtha Cracking Center Scheduling via Population-Based Multi-Scenario Planning},author={Yoon, Deunsol and Hong, Sunghoon and Jung, Whiyoung and Lee, Kanghoon and Lim, Woohyung},booktitle={IJCAI 2025 Workshop: Agent AI for Scenario Planning (AgentScen)},year={2025},}
ICML
Agent-Centric Actor-Critic for Asynchronous Multi-Agent Reinforcement Learning
Whiyoung Jung*, Sunghoon Hong*, Deunsol Yoon*, Kanghoon Lee, and 1 more author
In International Conference on Machine Learning (ICML), 2025
@inproceedings{jung2025agent,title={Agent-Centric Actor-Critic for Asynchronous Multi-Agent Reinforcement Learning},author={Jung, Whiyoung and Hong, Sunghoon and Yoon, Deunsol and Lee, Kanghoon and Lim, Woohyung},booktitle={International Conference on Machine Learning (ICML)},year={2025},}
ICML
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
Jeonghye Kim, Yongjae Shin, Whiyoung Jung, Sunghoon Hong, and 4 more authors
In International Conference on Machine Learning (ICML), 2025
@inproceedings{kim2025penalizing,title={Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data},author={Kim, Jeonghye and Shin, Yongjae and Jung, Whiyoung and Hong, Sunghoon and Yoon, Deunsol and Sung, Youngchul and Lee, Kanghoon and Lim, Woohyung},booktitle={International Conference on Machine Learning (ICML)},year={2025},note={Spotlight (2.6%)},}
ICML
Online Pre-Training for Offline-to-Online Reinforcement Learning
Yongjae Shin, Jeonghye Kim, Whiyoung Jung, Sunghoon Hong, and 7 more authors
In International Conference on Machine Learning (ICML), 2025
@inproceedings{shin2025online,title={Online Pre-Training for Offline-to-Online Reinforcement Learning},author={Shin, Yongjae and Kim, Jeonghye and Jung, Whiyoung and Hong, Sunghoon and Yoon, Deunsol and Jang, Youngsoo and Kim, Geon-Hyeong and Chae, Jongseong and Sung, Youngchul and Lee, Kanghoon and Lim, Woohyung},booktitle={International Conference on Machine Learning (ICML)},year={2025},}
2024
AAMAS Workshop
Agent-Oriented Centralized Critic for Asynchronous Multi-Agent Reinforcement Learning
Sunghoon Hong*, Whiyoung Jung*, Deunsol Yoon*, Kanghoon Lee, and 1 more author
In AAMAS 2024 Workshop: Adaptive Learning and Agents (ALA), 2024
@inproceedings{hong2024agent,title={Agent-Oriented Centralized Critic for Asynchronous Multi-Agent Reinforcement Learning},author={Hong, Sunghoon and Jung, Whiyoung and Yoon, Deunsol and Lee, Kanghoon and Lim, Woohyung},booktitle={AAMAS 2024 Workshop: Adaptive Learning and Agents (ALA)},year={2024},}
AAMAS
Naphtha Cracking Center Scheduling Optimization using Multi-Agent Reinforcement Learning
Sunghoon Hong, Deunsol Yoon, Whiyoung Jung, Jinsang Lee, and 8 more authors
In Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2024
@inproceedings{hong2024naphtha,title={Naphtha Cracking Center Scheduling Optimization using Multi-Agent Reinforcement Learning},author={Hong, Sunghoon and Yoon, Deunsol and Jung, Whiyoung and Lee, Jinsang and Yoo, Hyundam and Ham, Jiwon and Jung, Suhyun and Moon, Chanwoo and Jung, Yeontae Jung and Lee, Kanghoon and Lim, Woohyung and others},booktitle={Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS)},year={2024},}
2023
ICML Workshop
Hierarchical Decomposition Framework for Feasibility-hard Combinatorial Optimization
Hanbum Ko, Minu Kim, Han-Seul Jeong, Sunghoon Hong, and 4 more authors
In ICML 2023 Workshop: Sampling and Optimization in Discrete Space (SODS), 2023
@inproceedings{ko2023hierarchical,title={Hierarchical Decomposition Framework for Feasibility-hard Combinatorial Optimization},author={Ko, Hanbum and Kim, Minu and Jeong, Han-Seul and Hong, Sunghoon and Yoon, Deunsol and Park, Youngjoon and Lim, Woohyung and others},booktitle={ICML 2023 Workshop: Sampling and Optimization in Discrete Space (SODS)},year={2023},}
2022
ICLR
Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
Sunghoon Hong, Deunsol Yoon, and Kee-Eung Kim
In International Conference on Learning Representations (ICLR), 2022
@inproceedings{hong2022structure,title={Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning},author={Hong, Sunghoon and Yoon, Deunsol and Kim, Kee-Eung},booktitle={International Conference on Learning Representations (ICLR)},year={2022},}
NeurIPS Workshop
ReSPack: A Large-Scale Rectilinear Steiner Tree Packing Data Generator and Benchmark
Kanghoon Lee, Youngjoon Park, Han-Seul Jeong, Sunghoon Hong, and 3 more authors
@inproceedings{lee2022respack,title={ReSPack: A Large-Scale Rectilinear Steiner Tree Packing Data Generator and Benchmark},author={Lee, Kanghoon and Park, Youngjoon and Jeong, Han-Seul and Hong, Sunghoon and Yoon, Deunsol and Sohn, Sungryull and others},booktitle={NeurIPS 2022 Workshop: SyntheticData4ML},year={2022},}
2021
ICLR
Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic
Deunsol Yoon*, Sunghoon Hong*, Byung-Jun Lee, and Kee-Eung Kim
In International Conference on Learning Representations (ICLR), 2021
@inproceedings{yoon2021winning,title={Winning the L2RPN Challenge: Power Grid Management via Semi-Markov Afterstate Actor-Critic},author={Yoon, Deunsol and Hong, Sunghoon and Lee, Byung-Jun and Kim, Kee-Eung},booktitle={International Conference on Learning Representations (ICLR)},year={2021},note={Spotlight (5%)},}
