400 citations · 1.2k across the 67 of their papers we have counts for
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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-…
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…