5 citations · 10 across the 5 of their papers we have counts for
5 papers
Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning
Xuehui Yu, Mhairi Dunion, Xin Li +1
Meta-Reinforcement Learning (Meta-RL) agents can struggle to operate across tasks with varying environmental features that require different optimal skills (i.e., different modes o…
Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras
Mhairi Dunion, Stefano V. Albrecht
The performance of image-based Reinforcement Learning (RL) agents can vary depending on the position of the camera used to capture the images. Training on multiple cameras simultan…
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck +2
Reinforcement Learning (RL) environments can produce training data with spurious correlations between features due to the amount of training data or its limited feature coverage. T…
Deep Reinforcement Learning for Multi-Agent Interaction
Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho +14
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Tow…
Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning
Mhairi Dunion, Trevor McInroe, Kevin Sebastian Luck +2
Reinforcement Learning (RL) agents are often unable to generalise well to environment variations in the state space that were not observed during training. This issue is especially…