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Journal Articles
- 2024
[j3]Félix Chalumeau, Bryan Lim, Raphaël Boige, Maxime Allard, Luca Grillotti, Manon Flageat, Valentin Macé, Guillaume Richard, Arthur Flajolet, Thomas Pierrot, Antoine Cully:
QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration. J. Mach. Learn. Res. 25: 108:1-108:16 (2024)- [j2]Manon Flageat
, Antoine Cully:
Uncertain Quality-Diversity: Evaluation Methodology and New Methods for Quality-Diversity in Uncertain Domains. IEEE Trans. Evol. Comput. 28(4): 891-902 (2024) - 2023
- [j1]Manon Flageat, Félix Chalumeau, Antoine Cully:
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains. ACM Trans. Evol. Learn. Optim. 3(1): 1:1-1:32 (2023)
Conference and Workshop Papers
- 2024
- [c9]Manon Flageat, Bryan Lim, Antoine Cully:
Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms. AAAI 2024: 12024-12032 - [c8]Manon Flageat, Bryan Lim, Antoine Cully:
Enhancing MAP-Elites with Multiple Parallel Evolution Strategies. GECCO 2024 - [c7]Manon Flageat, Bryan Lim, Antoine Cully:
Evolutionary Reinforcement Learning. GECCO Companion 2024: 856-882 - 2023
- [c6]Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully:
MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. GECCO 2023: 138-146 - [c5]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: 156-164 - [c4]Bryan Lim, Manon Flageat, Antoine Cully:
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. GECCO 2023: 1212-1220 - [c3]Manon Flageat, Luca Grillotti, Antoine Cully:
Benchmark Tasks for Quality-Diversity Applied to Uncertain Domains. GECCO Companion 2023: 2157-2162 - 2020
- [c2]Manon Flageat, Kai Arulkumaran, Anil A. Bharath:
Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. ESANN 2020: 229-234 - [c1]Manon Flageat, Antoine Cully:
Fast and stable MAP-Elites in noisy domains using deep grids. ALIFE 2020: 273-282
Informal and Other Publications
- 2024
- [i16]Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully:
Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learning. CoRR abs/2401.08632 (2024) - [i15]Bryan Lim, Manon Flageat, Antoine Cully:
Large Language Models as In-context AI Generators for Quality-Diversity. CoRR abs/2404.15794 (2024) - [i14]Manon Flageat, Hannah Janmohamed, Bryan Lim, Antoine Cully:
Exploring the Performance-Reproducibility Trade-off in Quality-Diversity. CoRR abs/2409.13315 (2024) - 2023
- [i13]Manon Flageat, Antoine Cully:
Uncertain Quality-Diversity: Evaluation methodology and new methods for Quality-Diversity in Uncertain Domains. CoRR abs/2302.00463 (2023) - [i12]Maxence Faldor, Félix Chalumeau, Manon Flageat, Antoine Cully:
MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy. CoRR abs/2303.03832 (2023) - [i11]Manon Flageat, Bryan Lim, Antoine Cully:
Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies. CoRR abs/2303.06137 (2023) - [i10]Bryan Lim, Manon Flageat, Antoine Cully:
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning. CoRR abs/2303.06164 (2023) - [i9]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 abs/2304.03672 (2023) - [i8]Manon Flageat, Luca Grillotti, Antoine Cully:
Benchmark tasks for Quality-Diversity applied to Uncertain domains. CoRR abs/2304.12454 (2023) - [i7]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 abs/2308.03665 (2023) - [i6]Garðar Ingvarsson, Mikayel Samvelyan, Bryan Lim, Manon Flageat, Antoine Cully, Tim Rocktäschel:
Mix-ME: Quality-Diversity for Multi-Agent Learning. CoRR abs/2311.01829 (2023) - [i5]Manon Flageat, Bryan Lim, Antoine Cully:
Beyond Expected Return: Accounting for Policy Reproducibility when Evaluating Reinforcement Learning Algorithms. CoRR abs/2312.07178 (2023) - 2022
- [i4]Manon Flageat, Félix Chalumeau, Antoine Cully:
Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains. CoRR abs/2210.13156 (2022) - [i3]Manon Flageat, Bryan Lim, Luca Grillotti, Maxime Allard, Simón C. Smith, Antoine Cully:
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning. CoRR abs/2211.02193 (2022) - [i2]Bryan Lim, Manon Flageat, Antoine Cully:
Efficient Exploration using Model-Based Quality-Diversity with Gradients. CoRR abs/2211.12610 (2022) - 2020
- [i1]Manon Flageat, Antoine Cully:
Fast and stable MAP-Elites in noisy domains using deep grids. CoRR abs/2006.14253 (2020)
Coauthor Index
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