9 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.NI2020★ 9 cited
A Reinforcement Learning Formulation of the Lyapunov Optimization: Application to Edge Computing Systems with Queue Stability
Sohee Bae, Seungyul Han, Youngchul Sung
In this paper, a deep reinforcement learning (DRL)-based approach to the Lyapunov optimization is considered to minimize the time-average penalty while maintaining queue stability.…
cs.LG2020★ 3 cited
Cross-Domain Imitation Learning with a Dual Structure
Sungho Choi, Seungyul Han, Woojun Kim +1
In this paper, we consider cross-domain imitation learning (CDIL) in which an agent in a target domain learns a policy to perform well in the target domain by observing expert demo…
cs.LG2019★ 5 cited
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
Seungyul Han, Youngchul Sung
In importance sampling (IS)-based reinforcement learning algorithms such as Proximal Policy Optimization (PPO), IS weights are typically clipped to avoid large variance in learning…