400 citations · 1.2k across the 67 of their papers we have counts for
14 papers · 1 filter
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…
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-…
LeNSE: Learning To Navigate Subgraph Embeddings for Large-Scale Combinatorial Optimisation
David Ireland, Giovanni Montana
Combinatorial Optimisation problems arise in several application domains and are often formulated in terms of graphs. Many of these problems are NP-hard, but exact solutions are no…