3 papers
cs.LG2025
Leveraging weights signals -- Predicting and improving generalizability in reinforcement learning
Olivier Moulin, Vincent Francois-lavet, Paul Elbers +1
Generalizability of Reinforcement Learning (RL) agents (ability to perform on environments different from the ones they have been trained on) is a key problem as agents have the te…
cs.AI2022
Improving generalization in reinforcement learning through forked agents
Olivier Moulin, Vincent Francois-Lavet, Mark Hoogendoorn
An eco-system of agents each having their own policy with some, but limited, generalizability has proven to be a reliable approach to increase generalization across procedurally ge…
cs.AI2022
Improving generalization to new environments and removing catastrophic forgetting in Reinforcement Learning by using an eco-system of agents
Olivier Moulin, Vincent Francois-Lavet, Paul Elbers +1
Adapting a Reinforcement Learning (RL) agent to an unseen environment is a difficult task due to typical over-fitting on the training environment. RL agents are often capable of so…