91 citations · 142 across the 5 of their papers we have counts for
5 papers
Sequential annotations for naturally-occurring HRI: first insights
Lucien Tisserand, Frédéric Armetta, Heike Baldauf-Quilliatre +3
We explain the methodology we developed for improving the interactions accomplished by an embedded conversational agent, drawing from Conversation Analytic sequential and multimoda…
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…
DisTop: Discovering a Topological representation to learn diverse and rewarding skills
Arthur Aubret, Laetitia matignon, Salima Hassas
The optimal way for a deep reinforcement learning (DRL) agent to explore is to learn a set of skills that achieves a uniform distribution of states. Following this,we introduce Dis…
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…