91 citations · 142 across the 3 of their papers we have counts for
3 papers
An information-theoretic perspective on intrinsic motivation in reinforcement learning: a survey
Arthur Aubret, Laetitia Matignon, Salima Hassas
The reinforcement learning (RL) research area is very active, with an important number of new contributions; especially considering the emergent field of deep RL (DRL). However a n…
ELSIM: End-to-end learning of reusable skills through intrinsic motivation
Arthur Aubret, Laetitia Matignon, Salima Hassas
Taking inspiration from developmental learning, we present a novel reinforcement learning architecture which hierarchically learns and represents self-generated skills in an end-to…
A survey on intrinsic motivation in reinforcement learning
Arthur Aubret, Laetitia Matignon, Salima Hassas
The reinforcement learning (RL) research area is very active, with an important number of new contributions; especially considering the emergent field of deep RL (DRL). However a n…