1 citations · 1 across the 5 of their papers we have counts for
3 papers
cs.LG2025
From Sparse to Dense: Toddler-inspired Reward Transition in Goal-Oriented Reinforcement Learning
Junseok Park, Hyeonseo Yang, Min Whoo Lee +3
Reinforcement learning (RL) agents often face challenges in balancing exploration and exploitation, particularly in environments where sparse or dense rewards bias learning. Biolog…
cs.MA2025
Communicating Unexpectedness for Out-of-Distribution Multi-Agent Reinforcement Learning
Min Whoo Lee, Kibeom Kim, Soo Wung Shin +2
Applying multi-agent reinforcement learning methods to realistic settings is challenging as it may require the agents to quickly adapt to unexpected situations that are rarely or n…
cs.LG2021★ 1 cited
Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning
Kibeom Kim, Min Whoo Lee, Yoonsung Kim +3
Learning in a multi-target environment without prior knowledge about the targets requires a large amount of samples and makes generalization difficult. To solve this problem, it is…