| 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 | 34 | 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 | 18 | 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 | 14 | 2022 |
| Uncertain quality-diversity: Evaluation methodology and new methods for quality-diversity in uncertain domains M Flageat, A Cully IEEE Transactions on Evolutionary Computation, 2023 | 10 | 2023 |
| 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 | 6 | 2023 |
| 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 | 5 | 2024 |
| Efficient exploration using model-based quality-diversity with gradients B Lim, M Flageat, A Cully Artificial Life Conference Proceedings 35 2023 (1), 4, 2023 | 3 | 2023 |
| 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 | 3 | 2023 |
| 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 | 2 | 2023 |
| Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control. M Flageat, K Arulkumaran, AA Bharath ESANN, 229-234, 2020 | 2 | 2020 |
| 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 | 1 | 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 | | 2024 |
| Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learning M Faldor, F Chalumeau, M Flageat, A Cully arXiv preprint arXiv:2401.08632, 2023 | | 2023 |
| 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 |
| Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies M Flageat, B Lim, A Cully arXiv preprint arXiv:2303.06137, 2023 | | 2023 |
