Manon Flageat

Amanda Prorok

CoRR, December, 2025

Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learning.

[BibT_eX]

[DOI]

ACM Trans. Evol. Learn. Optim., 2025

Extract-QD Framework: A Generic Approach for Quality-Diversity in Noisy, Stochastic or Uncertain Domains.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2025

Evolutionary Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2025

2024

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

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., August, 2024

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

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2024

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

[BibT_eX]

[DOI]

CoRR, 2024

Evolutionary Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Enhancing MAP-Elites with Multiple Parallel Evolution Strategies.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

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

[BibT_eX]

[DOI]

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

2023

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

[BibT_eX]

[DOI]

Félix Chalumeau

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

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

CoRR, 2023

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

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Benchmark Tasks for Quality-Diversity Applied to Uncertain Domains.

[BibT_eX]

[DOI]

Luca Grillotti

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.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

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

[BibT_eX]

[DOI]

CoRR, 2022

Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

2020

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

[BibT_eX]

[DOI]

Proceedings of the 2020 Conference on Artificial Life, 2020

Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control.

[BibT_eX]

[DOI]