Publications

Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell (2022). imitation: Clean Imitation Learning Implementations. arXiv.

Tony Wang, Adam Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Michael Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell (2022). Adversarial Policies Beat Superhuman Go AIs. ICML.

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Erik Jenner, Herke Van Hoof, Adam Gleave (2022). Calculus on MDPs: Potential Shaping as a Gradient. arXiv.

Pavel Czempin, Adam Gleave (2022). Reducing Exploitability with Population Based Training. arXiv.

Adam Gleave, Sam Toyer (2022). A Primer on Maximum Causal Entropy Inverse Reinforcement Learning. arXiv.

Adam Gleave, Geoffrey Irving (2022). Uncertainty Estimation for Language Reward Models. arXiv.

Joar Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, Adam Gleave (2022). Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. ICML.

Erik Jenner, Adam Gleave (2021). Preprocessing Reward Functions for Interpretability. Cooperative AI Workshop at NeurIPS.

Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, Noah Dormann (2021). Stable-Baselines3: Reliable Reinforcement Learning Implementations. JMLR.

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Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike (2021). Quantifying Differences in Reward Functions. ICLR (Spotlight Paper).

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Eric J. Michaud, Adam Gleave, Stuart Russell (2020). Understanding Learned Reward Functions. DeepRL Workshop at NeurIPS.

Pedro Freire, Adam Gleave, Sam Toyer, Stuart Russell (2020). DERAIL: Diagnostic Environments for Reward And Imitation Learning. DeepRL Workshop at NeurIPS.

Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell (2020). Adversarial Policies: Attacking Deep Reinforcement Learning. ICLR.

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Aaron Tucker, Adam Gleave, Stuart Russell (2018). Inverse Reinforcement Learning for Video Games. DeepRL Workshop at NeurIPS.

Adam Gleave, Oliver Habryka (2018). Multi-task Maximum Causal Entropy Inverse Reinforcement Learning. GoalsRL Workshop at ICML.

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Sören Mindermann, Rohin Shah, Adam Gleave, Dylan Hadfield-Menell (2018). Active Inverse Reward Design. GoalsRL Workshop at ICML.

Adam Gleave, Christian Steinruecken (2017). Making Compression Algorithms for Unicode Text. Data Compression Conference.

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Ionel Gog, Malte Schwarzkopf, Adam Gleave, Robert Watson, Steven Hand (2016). Firmament: Fast, Centralized Cluster Scheduling at Scale. OSDI.

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