2 citations · 2 across the 14 of their papers we have counts for
5 papers · 1 filter
Fully Byzantine-Resilient Multi-Agent Reinforcement Learning
Haejoon Lee, Dimitra Panagou
We study distributed Byzantine-resilient actor-critic multi-agent reinforcement learning (AC-MARL), where agents collectively learn policies through local interactions. Existing me…
Distributed Model-Based Diffusion For Scalable Multi-Robot Trajectory Optimization
Haejoon Lee, Xinyi Wang, Taekyung Kim +1
Trajectory optimization for multi-robot systems remains a critical challenge, particularly when navigating highly non-convex, non-linear, and non-differentiable environments. While…
Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach
Daniel M. Cherenson, Haejoon Lee, Taekyung Kim +1
We study how to ensure probabilistic safety for nonlinear systems under distributional ambiguity. Our approach builds on a backup-based safety filtering framework that switches bet…
Robust Multi-Agent LLMs under Byzantine Faults
Haejoon Lee, Vincent-Daniel Yun, Dimitra Panagou +1
Large language model (LLM) agents increasingly collaborate over peer-to-peer networks to improve their reliability. However, these same interactions can also introduce vulnerabilit…
Fully Byzantine-Resilient Distributed Multi-Agent Q-Learning
Haejoon Lee, Dimitra Panagou
We study Byzantine-resilient distributed multi-agent reinforcement learning (MARL), where agents collaboratively learn optimal value functions over a compromised communication netw…