1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2026★ 1 cited
Toward a Unified Lyapunov-Certified ODE Convergence Analysis of Smooth Q-Learning with p-Norms
Donghwan Lee, Hyunjun Na
Convergence of Q-learning has been the subject of extensive study for decades. Among the available techniques, the ordinary differential equation (ODE) method is particularly appea…
cs.LG2026
Safe-Support Q-Learning: Learning without Unsafe Exploration
Yeeun Lim, Narim Jeong, Donghwan Lee
Ensuring safety during reinforcement learning (RL) training is critical in real-world applications where unsafe exploration can lead to devastating outcomes. While most safe RL met…
cs.LG2026
Finite-Time Analysis of Q-Value Iteration for General-Sum Stackelberg Games
Narim Jeong, Donghwan Lee
Reinforcement learning has been successful both empirically and theoretically in single-agent settings, but extending these results to multi-agent reinforcement learning in general…