Manon Flageat

According to our database, Manon Flageat authored at least 20 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Uncertain Quality-Diversity: Evaluation Methodology and New Methods for Quality-Diversity in Uncertain Domains.

Manon Flageat, Antoine Cully

IEEE Trans. Evol. Comput., August, 2024

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

Félix Chalumeau, Bryan Lim, Raphaël Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Guillaume Richard, Arthur Flajolet, Thomas Pierrot, Antoine Cully

J. Mach. Learn. Res., 2024

Exploring the Performance-Reproducibility Trade-off in Quality-Diversity.

Manon Flageat, Hannah Janmohamed, Bryan Lim, Antoine Cully

CoRR, 2024

Large Language Models as In-context AI Generators for Quality-Diversity.

Bryan Lim, Manon Flageat, Antoine Cully

CoRR, 2024

Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learning.

Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully

CoRR, 2024

Evolutionary Reinforcement Learning.

Manon Flageat, Bryan Lim, Antoine Cully

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Enhancing MAP-Elites with Multiple Parallel Evolution Strategies.

Manon Flageat, Bryan Lim, Antoine Cully

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms.

Manon Flageat, Bryan Lim, Antoine Cully

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains.

Manon Flageat, Félix Chalumeau, Antoine Cully

ACM Trans. Evol. Learn. Optim., March, 2023

Mix-ME: Quality-Diversity for Multi-Agent Learning.

Garðar Ingvarsson, Mikayel Samvelyan, Bryan Lim, Manon Flageat, Antoine Cully, Tim Rocktäschel

CoRR, 2023

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

Félix Chalumeau, Bryan Lim, Raphaël Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Arthur Flajolet, Thomas Pierrot, Antoine Cully

CoRR, 2023

Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies.

Manon Flageat, Bryan Lim, Antoine Cully

CoRR, 2023

Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning.

Bryan Lim, Manon Flageat, Antoine Cully

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains.

Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Benchmark Tasks for Quality-Diversity Applied to Uncertain Domains.

Manon Flageat, Luca Grillotti, Antoine Cully

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy.

Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Efficient Exploration using Model-Based Quality-Diversity with Gradients.

Bryan Lim, Manon Flageat, Antoine Cully

CoRR, 2022

Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning.

Manon Flageat, Bryan Lim, Luca Grillotti, Maxime Allard, Simón C. Smith, Antoine Cully

CoRR, 2022

2020

Fast and stable MAP-Elites in noisy domains using deep grids.

Manon Flageat, Antoine Cully

Proceedings of the 2020 Conference on Artificial Life, 2020

Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control.

Manon Flageat, Kai Arulkumaran, Anil A. Bharath

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020