6 citations · 6 across the 2 of their papers we have counts for
4 papers
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics
Stephane Doncieux, Nicolas Bredeche, Léni Le Goff +9
Robots are still limited to controlled conditions, that the robot designer knows with enough details to endow the robot with the appropriate models or behaviors. Learning algorithm…
Coping with the variability in humans reward during simulated human-robot interactions through the coordination of multiple learning strategies
Rémi Dromnelle, Benoît Girard, Erwan Renaudo +2
An important current challenge in Human-Robot Interaction (HRI) is to enable robots to learn on-the-fly from human feedback. However, humans show a great variability in the way the…
How to reduce computation time while sparing performance during robot navigation? A neuro-inspired architecture for autonomous shifting between model-based and model-free learning
Rémi Dromnelle, Erwan Renaudo, Guillaume Pourcel +3
Taking inspiration from how the brain coordinates multiple learning systems is an appealing strategy to endow robots with more flexibility. One of the expected advantages would be…
A Deep Learning Approach for Multi-View Engagement Estimation of Children in a Child-Robot Joint Attention task
Jack Hadfield, Georgia Chalvatzaki, Petros Koutras +3
In this work we tackle the problem of child engagement estimation while children freely interact with a robot in their room. We propose a deep-based multi-view solution that takes…