% Key papers for Intrinsically motivated exploration (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_curiosity_36124,
  title = {{Curiosity-driven Exploration by Self-supervised Prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/478},
}

@inproceedings{aaai2018_deep_101242,
  title = {{Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11485},
}

@inproceedings{iclr2017_learning_28290,
  title = {{Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=Hyq4yhile},
}

@inproceedings{iclr2017_learning_28352,
  title = {{Learning to Perform Physics Experiments via Deep Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=r1nTpv9eg},
}

@inproceedings{aaai2017_dynamic_104541,
  title = {{Dynamic Action Repetition for Deep Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10918},
}

@inproceedings{neurips2020_language_60138,
  title = {{Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18622},
}

@inproceedings{icml2019_curious_37205,
  title = {{CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3722},
}

@inproceedings{neurips2020_safe_60771,
  title = {{Safe Reinforcement Learning via Curriculum Induction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17616},
}

@inproceedings{icml2018_composable_36583,
  title = {{Composable Planning with Attributes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2348},
}

@inproceedings{neurips2018_occam_57452,
  title = {{Occam's razor is insufficient to infer the preferences of irrational agents}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11546},
}

@inproceedings{aaai2022_curiosity_1908,
  title = {{Curiosity-Driven Exploration via Latent Bayesian Surprise}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07752-curiosity-driven-exploration-via-latent-bayesian-surprise/},
}

@inproceedings{icml2020_what_38932,
  title = {{What can I do here? A Theory of Affordances in Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6274},
}

@inproceedings{neurips2019_learning_58535,
  title = {{Learning to Predict Without Looking Ahead: World Models Without Forward Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13672},
}

@inproceedings{aaai2018_interactively_101245,
  title = {{Interactively Learning a Blend of Goal-Based and Procedural Tasks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11488},
}

@inproceedings{aaai2021_relative_1262,
  title = {{Relative Variational Intrinsic Control}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/06732-relative-variational-intrinsic-control/},
}

@inproceedings{iclr2021_learning_30361,
  title = {{Learning Generalizable Visual Representations via Interactive Gameplay}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2685},
}

@inproceedings{neurips2021_information_62006,
  title = {{Information is Power: Intrinsic Control via Information Capture}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26332},
}

@inproceedings{iclr2018_learning_28420,
  title = {{Learning to Multi-Task by Active Sampling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/257},
}

@inproceedings{neurips2019_interval_58428,
  title = {{Interval timing in deep reinforcement learning agents}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13776},
}

@inproceedings{aaai2020_bar_101295,
  title = {{BAR — A Reinforcement Learning Agent for Bounding-Box Automated Refinement}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5639},
}

@inproceedings{icml2025_position_46068,
  title = {{Position: Truly Self-Improving Agents Require Intrinsic Metacognitive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/40177},
}

@inproceedings{iclr2024_robust_35294,
  title = {{Robust agents learn causal world models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17779},
}

@inproceedings{aaai2024_peer_6940,
  title = {{Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29061},
}

@inproceedings{icml2024_learning_43576,
  title = {{Learning to Model the World With Language}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34876},
}

@inproceedings{neurips2024_latent_71356,
  title = {{Latent Learning Progress Drives Autonomous Goal Selection in Human Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95893},
}

@inproceedings{aaai2024_generalising_6110,
  title = {{Generalising Planning Environment Redesign}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30003},
}

@inproceedings{iclr2024_skill_35354,
  title = {{Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17719},
}

@inproceedings{neurips2024_artificial_73953,
  title = {{Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93559},
}

@inproceedings{aaai2024_learning_6479,
  title = {{Learning Representations for Robust Human-Robot Interaction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30289},
}

@inproceedings{aaai2025_deep_8680,
  title = {{Deep Reinforcement Learning with Time-Scale Invariant Memory}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32124},
}

@inproceedings{aaai2025_learning_9751,
  title = {{Learning Structured World Models From and For Physical Interactions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35112},
}

@inproceedings{aaai2025_reasoning_10480,
  title = {{Reasoning About Actual Causes in Nondeterministic Domains}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33647},
}

@inproceedings{iclr2026_theory_84960,
  title = {{Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=8iPwqr6Adk},
}

@inproceedings{aaai2026_learning_107842,
  title = {{Learning to Cooperate with Minimal Observability}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40194},
}

@inproceedings{aaai2025_vision_11251,
  title = {{Vision-Based Generic Potential Function for Policy Alignment in Multi-Agent Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34123},
}

@inproceedings{icml2026_agent_51513,
  title = {{Agent Learning via Early Experience}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=N3dXUHY5dD},
}

@inproceedings{icml2026_goal_54680,
  title = {{Goal-Conditioned Agents that Learn Everything All at Once}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=rQxW0hnXYh},
}

@inproceedings{neurips2025_heterogeneous_75474,
  title = {{Heterogeneous Adversarial Play in Interactive Environments}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=8Q4xTf2SYC},
}

@inproceedings{neurips2025_intrinsic_78570,
  title = {{Intrinsic Goals for Autonomous Agents: Model-Based Exploration in Virtual Zebrafish Predicts Ethological Behavior and Whole-Brain Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=g2vViuEVDS},
}

@inproceedings{neurips2025_what_79679,
  title = {{What do you know? Bayesian knowledge inference for navigating agents}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rqXEiXZT6C},
}