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Mastering Diverse Domains through World Models

Danijar Hafner, Jurgis Pasukonis, Jimmy Ba, Timothy Lillicrap, 2023 — paper

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GAIL / VAIL

Generative Adversarial Imitation Learning
Jonathan Ho, Stefano Ermon, NeurIPS 2016 — paper

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow
Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, Sergey Levine, ICLR 2019 — paper

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A Distributional Perspective on Reinforcement Learning

Marc G. Bellemare, Will Dabney, Rémi Munos, ICML 2017 — paper

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Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine, ICML 2018 — paper

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Hyperspherical Normalization for Scalable Deep Reinforcement Learning

Hojoon Lee, Youngdo Lee, Takuma Seno, Donghu Kim, Peter Stone, Jaegul Choo, ICML 2025 — paper

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Bigger, Better, Faster: Human-level Atari with human-level efficiency

Max Schwarzer, Johan Obando-Ceron, Aaron Courville, Marc G. Bellemare, Rishabh Agarwal, Pablo Samuel Castro, ICML 2023 — paper

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Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

Julian Schrittwieser et al., Nature 2020 — paper

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this list will grow. slowly.