research
∙
09/19/2022
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey
The reinforcement learning (RL) research area is very active, with an im...
share
research
∙
07/27/2022
Time to augment contrastive learning
Biological vision systems are unparalleled in their ability to learn vis...
research
∙
05/12/2022
Embodied vision for learning object representations
Recent time-contrastive learning approaches manage to learn invariant ob...
research
∙
06/06/2021
DisTop: Discovering a Topological representation to learn diverse and rewarding skills
The optimal way for a deep reinforcement learning (DRL) agent to explore...
research
∙
06/23/2020
ELSIM: End-to-end learning of reusable skills through intrinsic motivation
Taking inspiration from developmental learning, we present a novel reinf...
research
∙
08/19/2019
