13 citations · 41 across the 15 of their papers we have counts for
4 papers · 1 filter
A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems
Hai V. Nguyen, Tan Bui-Thanh
Real-time accurate solutions of large-scale complex dynamical systems are in critical need for control, optimization, uncertainty quantification, and decision-making in practical e…
BADDr: Bayes-Adaptive Deep Dropout RL for POMDPs
Sammie Katt, Hai Nguyen, Frans A. Oliehoek +1
While reinforcement learning (RL) has made great advances in scalability, exploration and partial observability are still active research topics. In contrast, Bayesian RL (BRL) pro…
Recurrent Off-policy Baselines for Memory-based Continuous Control
Zhihan Yang, Hai Nguyen
When the environment is partially observable (PO), a deep reinforcement learning (RL) agent must learn a suitable temporal representation of the entire history in addition to a str…
Review, Analysis and Design of a Comprehensive Deep Reinforcement Learning Framework
Ngoc Duy Nguyen, Thanh Thi Nguyen, Hai Nguyen +2
The integration of deep learning to reinforcement learning (RL) has enabled RL to perform efficiently in high-dimensional environments. Deep RL methods have been applied to solve m…