% Key papers for Mean-field game learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2018_mean_36844,
  title = {{Mean Field Multi-Agent Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2458},
}

@inproceedings{aaai2020_on_102705,
  title = {{On the Convergence of Model Free Learning in Mean Field Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6203},
}

@inproceedings{iclr2020_actor_29426,
  title = {{Actor-Critic Provably Finds Nash Equilibria of Linear-Quadratic Mean-Field Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=H1lhqpEYPr},
}

@inproceedings{neurips2019_modelling_58621,
  title = {{Modelling the Dynamics of Multiagent Q-Learning in Repeated Symmetric Games: a Mean Field Theoretic Approach}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14177},
}

@inproceedings{aaai2022_generalization_2147,
  title = {{Generalization in Mean Field Games by Learning Master Policies}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09413-generalization-in-mean-field-games-by-learning-master-policies/},
}

@inproceedings{neurips2019_learning_58490,
  title = {{Learning Mean-Field Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13641},
}

@inproceedings{icml2021_global_39391,
  title = {{Global Convergence of Policy Gradient for Linear-Quadratic Mean-Field Control/Game in Continuous Time}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8961},
}

@inproceedings{icml2020_low_38434,
  title = {{Low-Variance and Zero-Variance Baselines for Extensive-Form Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6002},
}

@inproceedings{neurips2022_a_64349,
  title = {{A Mean-Field Game Approach to Cloud Resource Management with Function Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54661},
}

@inproceedings{aaai2024_zero_7845,
  title = {{Zero-Sum Games between Mean-Field Teams: Reachability-Based Analysis under Mean-Field Sharing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28831},
}

@inproceedings{icml2023_policy_41747,
  title = {{Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/25208},
}

@inproceedings{aaai2025_bounded_8295,
  title = {{Bounded Rationality Equilibrium Learning in Mean Field Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33508},
}

@inproceedings{iclr2022_learning_30808,
  title = {{Learning Graphon Mean Field Games and Approximate Nash Equilibria}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/7112},
}

@inproceedings{neurips2023_on_68122,
  title = {{On Imitation in Mean-field Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71662},
}

@inproceedings{iclr2023_population_32934,
  title = {{Population-size-Aware Policy Optimization for Mean-Field Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11293},
}

@inproceedings{iclr2024_learning_35706,
  title = {{Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17367},
}

@inproceedings{icml2026_population_54636,
  title = {{Population-Aware Imitation Learning in Mean-field Games with Common Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=qzzBvD3BOM},
}

@inproceedings{neurips2025_scalable_76308,
  title = {{Scalable Neural Incentive Design with Parameterized Mean-Field Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=I3V0NC9BQK},
}

@inproceedings{neurips2025_solving_76490,
  title = {{Solving Continuous Mean Field Games: Deep Reinforcement Learning for Non-Stationary Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Jw5TFF3HkH},
}

@inproceedings{neurips2026_bench_91140,
  title = {{Bench-MFG: A Benchmark Suite for Learning in Stationary Mean Field Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/139725},
}

@inproceedings{neurips2026_learning_93014,
  title = {{Learning Large-Scale Competitive Team Behaviors with Mean-Field Interactions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150877},
}