Manon Flageat

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 26

Top Topics

Robotic Control

Reinforcement Learning

Quality Measures

Top Venues

GECCO Companion

IEEE Trans. Evol. Comput.

Publications

Manon Flageat, Bryan Lim, Antoine Cully
Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms. AAAI (2024)
Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully
Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learning. CoRR (2024)
Bryan Lim, Manon Flageat, Antoine Cully
Large Language Models as In-context AI Generators for Quality-Diversity. CoRR (2024)
Manon Flageat, Bryan Lim, Antoine Cully
Evolutionary Reinforcement Learning. GECCO Companion (2024)
Manon Flageat, Bryan Lim, Antoine Cully
Enhancing MAP-Elites with Multiple Parallel Evolution Strategies. GECCO (2024)
Manon Flageat, Antoine Cully
Uncertain Quality-Diversity: Evaluation Methodology and New Methods for Quality-Diversity in Uncertain Domains. IEEE Trans. Evol. Comput. 28 (4) (2024)
Manon Flageat, Félix Chalumeau, Antoine Cully
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains. ACM Trans. Evol. Learn. Optim. 3 (1) (2023)
Manon Flageat, Luca Grillotti, Antoine Cully
Benchmark Tasks for Quality-Diversity Applied to Uncertain Domains. GECCO Companion (2023)
Manon Flageat, Bryan Lim, Antoine Cully
Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies. CoRR (2023)
Manon Flageat, Luca Grillotti, Antoine Cully
Benchmark tasks for Quality-Diversity applied to Uncertain domains. CoRR (2023)
Bryan Lim, Manon Flageat, Antoine Cully
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. GECCO (2023)
Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully
Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains. GECCO (2023)
Manon Flageat, Antoine Cully
Uncertain Quality-Diversity: Evaluation methodology and new methods for Quality-Diversity in Uncertain Domains. CoRR (2023)
Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully
MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. GECCO (2023)
Luca Grillotti, Manon Flageat, Bryan Lim, Antoine Cully
Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains. CoRR (2023)
Manon Flageat, Bryan Lim, Antoine Cully
Beyond Expected Return: Accounting for Policy Reproducibility when Evaluating Reinforcement Learning Algorithms. CoRR (2023)
Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully
MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. CoRR (2023)
Garðar Ingvarsson, Mikayel Samvelyan, Bryan Lim, Manon Flageat, Antoine Cully, Tim Rocktäschel
Mix-ME: Quality-Diversity for Multi-Agent Learning. CoRR (2023)
Bryan Lim, Manon Flageat, Antoine Cully
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. CoRR (2023)
Félix Chalumeau, Bryan Lim, Raphaël Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Arthur Flajolet, Thomas Pierrot, Antoine Cully
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration. CoRR (2023)
Manon Flageat, Bryan Lim, Luca Grillotti, Maxime Allard, Simón C. Smith, Antoine Cully
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning. CoRR (2022)
Bryan Lim, Manon Flageat, Antoine Cully
Efficient Exploration using Model-Based Quality-Diversity with Gradients. CoRR (2022)
Manon Flageat, Félix Chalumeau, Antoine Cully
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains. CoRR (2022)
Manon Flageat, Antoine Cully
Fast and stable MAP-Elites in noisy domains using deep grids. ALIFE (2020)
Manon Flageat, Antoine Cully
Fast and stable MAP-Elites in noisy domains using deep grids. CoRR (2020)
Manon Flageat, Kai Arulkumaran, Anil A. Bharath
Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. ESANN (2020)