400 citations · 1.2k across the 67 of their papers we have counts for
72 papers
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks
George Watkins, Giovanni Montana, Juergen Branke
The graph colouring problem consists of assigning labels, or colours, to the vertices of a graph such that no two adjacent vertices share the same colour. In this work we investiga…
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning
Alex Beeson, Giovanni Montana
Offline reinforcement learning agents seek optimal policies from fixed data sets. With environmental interaction prohibited, agents face significant challenges in preventing errors…
Goal-conditioned Offline Reinforcement Learning through State Space Partitioning
Mianchu Wang, Yue Jin, Giovanni Montana
Offline reinforcement learning (RL) aims to infer sequential decision policies using only offline datasets. This is a particularly difficult setup, especially when learning to achi…
Model-based trajectory stitching for improved behavioural cloning and its applications
Charles A. Hepburn, Giovanni Montana
Behavioural cloning (BC) is a commonly used imitation learning method to infer a sequential decision-making policy from expert demonstrations. However, when the quality of the data…
Improving TD3-BC: Relaxed Policy Constraint for Offline Learning and Stable Online Fine-Tuning
Alex Beeson, Giovanni Montana
The ability to discover optimal behaviour from fixed data sets has the potential to transfer the successes of reinforcement learning (RL) to domains where data collection is acutel…
Model-based Trajectory Stitching for Improved Offline Reinforcement Learning
Charles A. Hepburn, Giovanni Montana
In many real-world applications, collecting large and high-quality datasets may be too costly or impractical. Offline reinforcement learning (RL) aims to infer an optimal decision-…