We present a novel approach to address the challenge of generalization i...
We investigate the use of transformer sequence models as dynamics models...
Being able to seamlessly generalize across different tasks is fundamenta...
Inverse reinforcement learning is a paradigm motivated by the goal of
le...
Humans have impressive generalization capabilities when it comes to
mani...
Learning for model based control can be sample-efficient and generalize ...
Scaling model-based inverse reinforcement learning (IRL) to real robotic...
We present a meta-learning approach based on learning an adaptive,
high-...
Curiosity as a means to explore during reinforcement learning problems h...