Few-shot model-based adaptation in noisy conditions

no code implementations • 16 Oct 2020 • Karol Arndt, Ali Ghadirzadeh, Murtaza Hazara, Ville Kyrki

Few-shot adaptation is a challenging problem in the context of simulation-to-real transfer in robotics, requiring safe and informative data collection.

Reinforcement Learning (RL)

Meta Reinforcement Learning for Sim-to-real Domain Adaptation

no code implementations • 16 Sep 2019 • Karol Arndt, Murtaza Hazara, Ali Ghadirzadeh, Ville Kyrki

Modern reinforcement learning methods suffer from low sample efficiency and unsafe exploration, making it infeasible to train robotic policies entirely on real hardware.

Domain Adaptation Meta-Learning +3