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cs.LG2025
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
Samuel Garcin, Trevor McInroe, Pablo Samuel Castro +4
Extracting relevant information from a stream of high-dimensional observations is a central challenge for deep reinforcement learning agents. Actor-critic algorithms add further co…
cs.LG2024
DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
Samuel Garcin, James Doran, Shangmin Guo +2
Autonomous agents trained using deep reinforcement learning (RL) often lack the ability to successfully generalise to new environments, even when these environments share character…
cs.LG2023
How the level sampling process impacts zero-shot generalisation in deep reinforcement learning
Samuel Garcin, James Doran, Shangmin Guo +2
A key limitation preventing the wider adoption of autonomous agents trained via deep reinforcement learning (RL) is their limited ability to generalise to new environments, even wh…