65 citations · 89 across the 5 of their papers we have counts for
5 papers
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…
Autonomous Goal Exploration using Learned Goal Spaces for Visuomotor Skill Acquisition in Robots
Adrien Laversanne-Finot, Alexandre Péré, Pierre-Yves Oudeyer
The automatic and efficient discovery of skills, without supervision, for long-living autonomous agents, remains a challenge of Artificial Intelligence. Intrinsically Motivated Goa…
Curiosity Driven Exploration of Learned Disentangled Goal Spaces
Adrien Laversanne-Finot, Alexandre Péré, Pierre-Yves Oudeyer
Intrinsically motivated goal exploration processes enable agents to autonomously sample goals to explore efficiently complex environments with high-dimensional continuous actions.…
Continuous-variable supraquantum nonlocality
Andreas Ketterer, Adrien Laversanne-Finot, Leandro Aolita
Supraquantum nonlocality refers to correlations that are more nonlocal than allowed by quantum theory but still physically conceivable in post-quantum theories, in the sense of res…
General conditions for maximal violation of non-contextuality in discrete and continuous variables
A. Laversanne-Finot, A. Ketterer, M. R. Barros +4
The contextuality of quantum mechanics, i.e. the measurement outcome dependence upon previously made measurements, can be shown by the violation of inequalities based on measuremen…