1 citations · 1 across the 5 of their papers we have counts for
5 papers
Dataset Clustering for Improved Offline Policy Learning
Qiang Wang, Yixin Deng, Francisco Roldan Sanchez +4
Offline policy learning aims to discover decision-making policies from previously-collected datasets without additional online interactions with the environment. As the training da…
Learning and reusing primitive behaviours to improve Hindsight Experience Replay sample efficiency
Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens +3
Hindsight Experience Replay (HER) is a technique used in reinforcement learning (RL) that has proven to be very efficient for training off-policy RL-based agents to solve goal-base…
Hierarchical reinforcement learning for in-hand robotic manipulation using Davenport chained rotations
Francisco Roldan Sanchez, Qiang Wang, David Cordova Bulens +3
End-to-end reinforcement learning techniques are among the most successful methods for robotic manipulation tasks. However, the training time required to find a good policy capable…
Towards advanced robotic manipulation
Francisco Roldan Sanchez, Stephen Redmond, Kevin McGuinness +1
Robotic manipulation and control has increased in importance in recent years. However, state of the art techniques still have limitations when required to operate in real world app…
Adaptive Target-Condition Neural Network: DNN-Aided Load Balancing for Hybrid LiFi and WiFi Networks
Han Ji, Qiang Wang, Stephen J. Redmond +2
Load balancing (LB) is a challenging issue in the hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks (HLWNets), due to the nature of heterogeneous access points (AP…