| Fast and stable MAP-Elites in noisy domains using deep grids M Flageat, A Cully ALIFE 2020: The 2020 Conference on Artificial Life - direct.mit.edu, 2020 | 44 | 2020 |
| Empirical analysis of pga-map-elites for neuroevolution in uncertain domains M Flageat, F Chalumeau, A Cully ACM Transactions on Evolutionary Learning 3 (1), 1-32, 2023 | 27 | 2023 |
| Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning M Flageat, B Lim, L Grillotti, M Allard, SC Smith, A Cully QD Benchmark Workshop - Gecco 2022, 2022 | 22 | 2022 |
| Qdax: A library for quality-diversity and population-based algorithms with hardware acceleration F Chalumeau, B Lim, R Boige, M Allard, L Grillotti, M Flageat, V Macé, ... Journal of Machine Learning Research 25 (108), 1-16, 2024 | 21 | 2024 |
| Map-elites with descriptor-conditioned gradients and archive distillation into a single policy M Faldor, F Chalumeau, M Flageat, A Cully Proceedings of the Genetic and Evolutionary Computation Conference, 138-146, 2023 | 19 | 2023 |
| Uncertain quality-diversity: Evaluation methodology and new methods for quality-diversity in uncertain domains M Flageat, A Cully IEEE Transactions on Evolutionary Computation, 2023 | 18 | 2023 |
| Synergizing quality-diversity with descriptor-conditioned reinforcement learning M Faldor, F Chalumeau, M Flageat, A Cully arXiv preprint arXiv:2401.08632, 2023 | 8 | 2023 |
| Large language models as in-context ai generators for quality-diversity B Lim, M Flageat, A Cully ALIFE 2024: Proceedings of the 2024 Artificial Life Conference, 2024 | 7 | 2024 |
| Don't bet on luck alone: Enhancing behavioral reproducibility of quality-diversity solutions in uncertain domains L Grillotti, M Flageat, B Lim, A Cully Proceedings of the Genetic and Evolutionary Computation Conference, 156-164, 2023 | 7 | 2023 |
| Understanding the synergies between quality-diversity and deep reinforcement learning B Lim, M Flageat, A Cully Proceedings of the Genetic and Evolutionary Computation Conference, 1212-1220, 2023 | 6 | 2023 |
| Enhancing MAP-Elites with Multiple Parallel Evolution Strategies M Flageat, B Lim, A Cully Proceedings of the Genetic and Evolutionary Computation Conference, 1082-1090, 2024 | 5* | 2024 |
| Efficient exploration using model-based quality-diversity with gradients B Lim, M Flageat, A Cully ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life …, 2023 | 5 | 2023 |
| Beyond expected return: accounting for policy reproducibility when evaluating reinforcement learning algorithms M Flageat, B Lim, A Cully Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12024 …, 2024 | 3 | 2024 |
| Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. M Flageat, K Arulkumaran, AA Bharath ESANN, 229-234, 2020 | 2 | 2020 |
| Exploring the Performance-Reproducibility Trade-off in Quality-Diversity M Flageat, H Janmohamed, B Lim, A Cully arXiv preprint arXiv:2409.13315, 2024 | 1 | 2024 |
| Mix-ME: Quality-Diversity for Multi-Agent Learning G Ingvarsson, M Samvelyan, B Lim, M Flageat, A Cully, T Rocktäschel arXiv preprint arXiv:2311.01829, 2023 | 1 | 2023 |
| Extract-QD Framework: A Generic Approach for Quality-Diversity in Noisy, Stochastic or Uncertain Domains M Flageat, J Huber, F Helenon, S Doncieux, A Cully arXiv preprint arXiv:2502.06585, 2025 | | 2025 |
| Evolutionary Reinforcement Learning M Flageat, B Lim, A Cully Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | | 2024 |
| Benchmark tasks for Quality-Diversity applied to Uncertain domains M Flageat, L Grillotti, A Cully Proceedings of the Companion Conference on Genetic and Evolutionary …, 2023 | | 2023 |
