4 papers · 1 filter
Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning
Sunwoo Lee, Mingu Kang, Yonghyeon Jo +1
Cooperation is central to multi-agent reinforcement learning (MARL), yet learned coordination can be fragile when external perturbations disrupt inter-agent interactions. Prior rob…
Shaping Zero-Shot Coordination via State Blocking
Mingu Kang, Sunwoo Lee, Yonghyeon Jo +1
Zero-shot coordination (ZSC) aims to enable agents to cooperate with independently trained partners without prior interaction, a key requirement for real-world multi-agent systems…
Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo +1
Traditional robust methods in multi-agent reinforcement learning (MARL) often struggle against coordinated adversarial attacks in cooperative scenarios. To address this limitation,…
Exclusively Penalized Q-learning for Offline Reinforcement Learning
Junghyuk Yeom, Yonghyeon Jo, Jungmo Kim +2
Constraint-based offline reinforcement learning (RL) involves policy constraints or imposing penalties on the value function to mitigate overestimation errors caused by distributio…