451 citations · 2.2k across the 99 of their papers we have counts for
17 papers · 1 filter
Autotelic Agents with Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey
Cédric Colas, Tristan Karch, Olivier Sigaud +1
Building autonomous machines that can explore open-ended environments, discover possible interactions and build repertoires of skills is a general objective of artificial intellige…
Meta Automatic Curriculum Learning
Rémy Portelas, Clément Romac, Katja Hofmann +1
A major challenge in the Deep RL (DRL) community is to train agents able to generalize their control policy over situations never seen in training. Training on diverse tasks has be…
EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models
Cédric Colas, Boris Hejblum, Sébastien Rouillon +4
Epidemiologists model the dynamics of epidemics in order to propose control strategies based on pharmaceutical and non-pharmaceutical interventions (contact limitation, lock down,…
Emergent Jaw Predominance in Vocal Development through Stochastic Optimization
Clément Moulin-Frier, Jules Brochard, Freek Stulp +1
Infant vocal babbling strongly relies on jaw oscillations, especially at the stage of canonical babbling, which underlies the syllabic structure of world languages. In this paper,…
GRIMGEP: Learning Progress for Robust Goal Sampling in Visual Deep Reinforcement Learning
Grgur Kovač, Adrien Laversanne-Finot, Pierre-Yves Oudeyer
Designing agents, capable of learning autonomously a wide range of skills is critical in order to increase the scope of reinforcement learning. It will both increase the diversity…
Hierarchically Organized Latent Modules for Exploratory Search in Morphogenetic Systems
Mayalen Etcheverry, Clement Moulin-Frier, Pierre-Yves Oudeyer
Self-organization of complex morphological patterns from local interactions is a fascinating phenomenon in many natural and artificial systems. In the artificial world, typical exa…