Robotic Control Using Model Based Meta Adaption
Karam Daaboul,Joel Ikels,J. Marius Zöllner,Karam Daaboul,Joel Ikels,J. Marius Zöllner
In machine learning, meta-learning methods aim for fast adaptability to unknown tasks using prior knowledge. Model-based meta-reinforcement learning combines reinforcement learning via world models with Meta Reinforcement Learning (MRL) for increased sample efficiency. However, adaption to unknown tasks does not always result in preferable agent behavior. This paper introduces a new Meta Adaptatio...
