331 citations · 823 across the 14 of their papers we have counts for
3 papers · 1 filter
Mixed Reinforcement Learning with Additive Stochastic Uncertainty
Yao Mu, Shengbo Eben Li, Chang Liu +4
Reinforcement learning (RL) methods often rely on massive exploration data to search optimal policies, and suffer from poor sampling efficiency. This paper presents a mixed reinfor…
Hierarchical Reinforcement Learning for Self-Driving Decision-Making without Reliance on Labeled Driving Data
Jingliang Duan, Shengbo Eben Li, Yang Guan +2
Decision making for self-driving cars is usually tackled by manually encoding rules from drivers' behaviors or imitating drivers' manipulation using supervised learning techniques.…
Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors
Jingliang Duan, Yang Guan, Shengbo Eben Li +2
In reinforcement learning (RL), function approximation errors are known to easily lead to the Q-value overestimations, thus greatly reducing policy performance. This paper presents…