% Key papers for Learning in Markov games (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2017_training_28267,
  title = {{Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=Hk3mPK5gg},
}

@inproceedings{neurips2018_multi_57394,
  title = {{Multi-Agent Generative Adversarial Imitation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11718},
}

@inproceedings{aaai2020_bi_102727,
  title = {{Bi-Level Actor-Critic for Multi-Agent Coordination}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6226},
}

@inproceedings{neurips2020_combining_59551,
  title = {{Combining Deep Reinforcement Learning and Search for Imperfect-Information Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17281},
}

@inproceedings{neurips2018_a_56794,
  title = {{A Deep Bayesian Policy Reuse Approach Against Non-Stationary Agents}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11116},
}

@inproceedings{aaai2021_exploration_570,
  title = {{Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/11263-exploration-exploitation-in-multi-agent-learning-catastrophe-theory-meets-game-theory/},
}

@inproceedings{icml2018_competitive_36581,
  title = {{Competitive Multi-agent Inverse Reinforcement Learning with Sub-optimal Demonstrations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2082},
}

@inproceedings{iclr2022_global_31556,
  title = {{Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/7008},
}

@inproceedings{icml2021_a_38986,
  title = {{A Sharp Analysis of Model-based Reinforcement Learning with Self-Play}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8981},
}

@inproceedings{aaai2016_selectively_105388,
  title = {{Selectively Reactive Coordination for a Team of Robot Soccer Champions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10415},
}

@inproceedings{neurips2020_model_60338,
  title = {{Model-Based Multi-Agent RL in Zero-Sum Markov Games with Near-Optimal Sample Complexity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18478},
}

@inproceedings{aaai2021_learning_873,
  title = {{Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04950-learning-game-theoretic-models-of-multiagent-trajectories-using-implicit-layers/},
}

@inproceedings{neurips2020_learning_60227,
  title = {{Learning to Incentivize Other Learning Agents}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17970},
}

@inproceedings{aaai2020_algorithmic_101995,
  title = {{Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5857},
}

@inproceedings{aaai2019_large_102681,
  title = {{Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4567},
}

@inproceedings{neurips2018_learning_57311,
  title = {{Learning in Games with Lossy Feedback}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11502},
}

@inproceedings{neurips2020_no_60424,
  title = {{No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18021},
}

@inproceedings{aaai2019_tackling_100765,
  title = {{Tackling Sparse Rewards in Real-Time Games with Statistical Forward Planning Methods}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3990},
}

@inproceedings{neurips2017_countering_56225,
  title = {{Countering Feedback Delays in Multi-Agent Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9388},
}

@inproceedings{neurips2019_non_58683,
  title = {{Non-Cooperative Inverse Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13985},
}

@inproceedings{aaai2024_accelerate_5110,
  title = {{Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29011},
}

@inproceedings{aaai2024_stability_7405,
  title = {{Stability of Multi-Agent Learning in Competitive Networks: Delaying the Onset of Chaos}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29692},
}

@inproceedings{aaai2025_learning_9741,
  title = {{Learning Nash Equilibrium of Markov Potential Games with a Shared Constraint via Primal-Dual Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33821},
}

@inproceedings{aaai2024_data_5592,
  title = {{Data Poisoning to Fake a Nash Equilibria for Markov Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29529},
}

@inproceedings{icml2025_incentivize_47930,
  title = {{Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44674},
}

@inproceedings{neurips2025_on_79586,
  title = {{On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=qu6mRbSnUs},
}

@inproceedings{aaai2025_asymptotic_8158,
  title = {{Asymptotic Extinction in Large Coordination Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33495},
}

@inproceedings{aaai2025_foundations_9226,
  title = {{Foundations of Multi-Agent Learning in Dynamic Environments: Where Reinforcement Learning Meets Strategic Decision-Making}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35127},
}

@inproceedings{aaai2025_synchronization_10885,
  title = {{Synchronization in Learning in Periodic Zero-Sum Games Triggers Divergence from Nash Equilibrium}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34485},
}

@inproceedings{iclr2024_loqa_33997,
  title = {{LOQA: Learning with Opponent Q-Learning Awareness}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19078},
}

@inproceedings{iclr2024_a_34213,
  title = {{A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18862},
}

@inproceedings{iclr2024_sample_35239,
  title = {{Sample-Efficient Multi-Agent RL: An Optimization Perspective}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17834},
}

@inproceedings{iclr2024_provable_35536,
  title = {{Provable Memory Efficient Self-Play Algorithm for Model-free Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17537},
}

@inproceedings{icml2024_zero_44515,
  title = {{Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33937},
}

@inproceedings{icml2024_sample_45447,
  title = {{Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33004},
}

@inproceedings{icml2025_prediction_46744,
  title = {{Prediction-Aware Learning in Multi-Agent Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45828},
}

@inproceedings{icml2025_breaking_48072,
  title = {{Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44535},
}

@inproceedings{icml2025_convex_49081,
  title = {{Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43543},
}

@inproceedings{icml2026_provably_51583,
  title = {{Provably Convergent Actor-Critic for MARL through Risk-aversion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=NpguYNGrG2},
}

@inproceedings{icml2026_multi_51887,
  title = {{Multi-agent imitation learning with function approximation: linear Markov games and beyond}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Qn2HcnC4l2},
}