1 code implementation • 7 Aug 2023 • Felix Chalumeau, Bryan Lim, Raphael Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Arthur Flajolet, Thomas Pierrot, Antoine Cully
QDax is an open-source library with a streamlined and modular API for Quality-Diversity (QD) optimization algorithms in Jax.
no code implementations • 27 Mar 2023 • Valentin Macé, Raphaël Boige, Felix Chalumeau, Thomas Pierrot, Guillaume Richard, Nicolas Perrin-Gilbert
In the context of neuroevolution, Quality-Diversity algorithms have proven effective in generating repertoires of diverse and efficient policies by relying on the definition of a behavior space.
no code implementations • 24 Nov 2022 • Felix Chalumeau, Thomas Pierrot, Valentin Macé, Arthur Flajolet, Karim Beguir, Antoine Cully, Nicolas Perrin-Gilbert
Exploration is at the heart of several domains trying to solve control problems such as Reinforcement Learning and QD methods are promising candidates to overcome the challenges associated.
1 code implementation • 24 Oct 2022 • Manon Flageat, Felix Chalumeau, Antoine Cully
Secondly, we show that in addition to outperforming all the considered baselines, the collections of solutions generated by PGA-MAP-Elites are highly reproducible in uncertain environments, approaching the reproducibility of solutions found by Quality-Diversity approaches built specifically for uncertain applications.
1 code implementation • 6 Oct 2022 • Felix Chalumeau, Raphael Boige, Bryan Lim, Valentin Macé, Maxime Allard, Arthur Flajolet, Antoine Cully, Thomas Pierrot
Recent work has shown that training a mixture of policies, as opposed to a single one, that are driven to explore different regions of the state-action space can address this shortcoming by generating a diverse set of behaviors, referred to as skills, that can be collectively used to great effect in adaptation tasks or for hierarchical planning.