2 papers
cs.AI2026
Improving Zero-Shot Offline RL via Behavioral Task Sampling
Nazim Bendib, Nicolas Perrin-Gilbert, Olivier Sigaud
Offline zero-shot reinforcement learning (RL) aims to learn agents that optimize unseen reward functions without additional environment interaction. The standard approach to this p…
cs.LG2025
Learning to explore when mistakes are not allowed
Charly Pecqueux-Guézénec, Stéphane Doncieux, Nicolas Perrin-Gilbert
Goal-Conditioned Reinforcement Learning (GCRL) provides a versatile framework for developing unified controllers capable of handling wide ranges of tasks, exploring environments, a…