12 citations · 30 across the 6 of their papers we have counts for
6 papers
Safe and Robust Reinforcement Learning: Principles and Practice
Taku Yamagata, Raul Santos-Rodriguez
Reinforcement Learning (RL) has shown remarkable success in solving relatively complex tasks, yet the deployment of RL systems in real-world scenarios poses significant challenges…
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations
Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez +5
In supervised learning, low quality annotations lead to poorly performing classification and detection models, while also rendering evaluation unreliable. This is particularly appa…
Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
Taku Yamagata, Ahmed Khalil, Raul Santos-Rodriguez
Recent works have shown that tackling offline reinforcement learning (RL) with a conditional policy produces promising results. The Decision Transformer (DT) combines the condition…
Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
Taku Yamagata, Ryan McConville, Raul Santos-Rodriguez
A promising approach to improve the robustness and exploration in Reinforcement Learning is collecting human feedback and that way incorporating prior knowledge of the target envir…
Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control
Taku Yamagata, Aisling O'Kane, Amid Ayobi +5
In this paper we investigate the use of model-based reinforcement learning to assist people with Type 1 Diabetes with insulin dose decisions. The proposed architecture consists of…
Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback
Taku Yamagata, Raúl Santos-Rodríguez, Ryan McConville +1
Recent advances in both machine learning and Internet-of-Things have attracted attention to automatic Activity Recognition, where users wear a device with sensors and their outputs…