most citedQDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration

10 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2023★ 10 cited

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration

Felix Chalumeau, Bryan Lim, Raphael Boige +7

QDax is an open-source library with a streamlined and modular API for Quality-Diversity (QD) optimization algorithms in Jax. The library serves as a versatile tool for optimization…

cs.AI2023

PASTA: Pretrained Action-State Transformer Agents

Raphael Boige, Yannis Flet-Berliac, Arthur Flajolet +2

Self-supervised learning has brought about a revolutionary paradigm shift in various computing domains, including NLP, vision, and biology. Recent approaches involve pre-training t…

cs.LG2023★ 3 cited

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX

Clément Bonnet, Daniel Luo, Donal Byrne +21

Open-source reinforcement learning (RL) environments have played a crucial role in driving progress in the development of AI algorithms. In modern RL research, there is a need for…

cs.AI2023★ 3 cited

Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces

Raphael Boige, Guillaume Richard, Jérémie Dona +2

Quality Diversity (QD) algorithms have been proposed to search for a large collection of both diverse and high-performing solutions instead of a single set of local optima. While e…

cs.NE2023★ 5 cited

The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers

Valentin Macé, Raphaël Boige, Felix Chalumeau +3

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 b…