118 citations · 200 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
On the Sensory Commutativity of Action Sequences for Embodied Agents
Hugo Caselles-Dupré, Michael Garcia-Ortiz, David Filliat
Perception of artificial agents is one the grand challenges of AI research. Deep Learning and data-driven approaches are successful on constrained problems where perception can be…
Don't forget, there is more than forgetting: new metrics for Continual Learning
Natalia Díaz-Rodríguez, Vincenzo Lomonaco, David Filliat +1
Continual learning consists of algorithms that learn from a stream of data/tasks continuously and adaptively thought time, enabling the incremental development of ever more complex…
State Representation Learning for Control: An Overview
Timothée Lesort, Natalia Díaz-Rodríguez, Jean-François Goudou +1
Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representatio…