Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
Federated Reinforcement Learning in Heterogeneous Environments
Ukjo Hwang, Songnam Hong
We investigate a Federated Reinforcement Learning with Environment Heterogeneity (FRL-EH) framework, where local environments exhibit statistical heterogeneity. Within this framewo…
cs.LG2025
Moderate Actor-Critic Methods: Controlling Overestimation Bias via Expectile Loss
Ukjo Hwang, Songnam Hong
Overestimation is a fundamental characteristic of model-free reinforcement learning (MF-RL), arising from the principles of temporal difference learning and the approximation of th…
cs.LG2023
On Practical Robust Reinforcement Learning: Practical Uncertainty Set and Double-Agent Algorithm
Ukjo Hwang, Songnam Hong
Robust reinforcement learning (RRL) aims at seeking a robust policy to optimize the worst case performance over an uncertainty set of Markov decision processes (MDPs). This set con…