Adversarial Policies: Attacking Deep Reinforcement Learning. - Adam Gleave; Michael Dennis 001; Cody Wild; Neel Kant; Sergey Levine; Stuart Russell 001 (ICLR, 2020)

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. - Michael Dennis 001; Natasha Jaques; Eugene Vinitsky; Alexandre M. Bayen; Stuart Russell 001; Andrew Critch; Sergey Levine (NeurIPS, 2020)

Accumulating Risk Capital Through Investing in Cooperation. - Charlotte Roman; Michael Dennis 001; Andrew Critch; Stuart Russell 001 (AAMAS, 2021)

Quantifying Differences in Reward Functions. - Adam Gleave; Michael Dennis 001; Shane Legg; Stuart Russell 001; Jan Leike (ICLR, 2021)

A New Formalism, Method and Open Issues for Zero-Shot Coordination. - Johannes Treutlein; Michael Dennis 001; Caspar Oesterheld; Jakob N. Foerster (ICML, 2021)

Replay-Guided Adversarial Environment Design. - Minqi Jiang; Michael Dennis 001; Jack Parker-Holder; Jakob N. Foerster; Edward Grefenstette; Tim Rocktäschel (NeurIPS, 2021)

Improving Social Welfare While Preserving Autonomy via a Pareto Mediator. - Stephen McAleer; John B. Lanier; Michael Dennis 001; Pierre Baldi; Roy Fox (CoRR, 2021)

The Stretch Factor of Hexagon-Delaunay Triangulations. - Ljubomir Perkovic; Michael Dennis 001; Duru Türkoglu (J. Comput. Geom., 2021)

Evolving Curricula with Regret-Based Environment Design. - Jack Parker-Holder; Minqi Jiang; Michael Dennis 001; Mikayel Samvelyan; Jakob N. Foerster; Edward Grefenstette; Tim Rocktäschel (ICML, 2022)

Grounding Aleatoric Uncertainty for Unsupervised Environment Design. - Minqi Jiang; Michael Dennis 001; Jack Parker-Holder; Andrei Lupu; Heinrich Küttler; Edward Grefenstette; Tim Rocktäschel; Jakob N. Foerster (NeurIPS, 2022)

Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles. - Thomas Krendl Gilbert; Aaron J. Snoswell; Michael Dennis 001; Rowan McAllister; Cathy Wu 002 (CoRR, 2022)

Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory. - Andrew Critch; Michael Dennis 001; Stuart Russell 001 (CoRR, 2022)

Adversarial Policies Beat Professional-Level Go AIs. - Tony Tong Wang; Adam Gleave; Nora Belrose; Tom Tseng; Joseph Miller; Michael D. Dennis; Yawen Duan; Viktor Pogrebniak; Sergey Levine; Stuart Russell 001 (CoRR, 2022)

The Benefits of Power Regularization in Cooperative Reinforcement Learning. - Michelle Li; Michael Dennis 001 (AAMAS, 2023)

Stabilizing Unsupervised Environment Design with a Learned Adversary. - Ishita Mediratta; Minqi Jiang; Jack Parker-Holder; Michael Dennis 001; Eugene Vinitsky; Tim Rocktäschel (CoLLAs, 2023)

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning. - Mikayel Samvelyan; Akbir Khan; Michael Dennis 001; Minqi Jiang; Jack Parker-Holder; Jakob Nicolaus Foerster; Roberta Raileanu; Tim Rocktäschel (ICLR, 2023)

Who Needs to Know? Minimal Knowledge for Optimal Coordination. - Niklas Lauffer; Ameesh Shah; Micah Carroll; Michael D. Dennis; Stuart Russell 001 (ICML, 2023)

Adversarial Policies Beat Superhuman Go AIs. - Tony Tong Wang; Adam Gleave; Tom Tseng; Kellin Pelrine; Nora Belrose; Joseph Miller; Michael D. Dennis; Yawen Duan; Viktor Pogrebniak; Sergey Levine; Stuart Russell 001 (ICML, 2023)

minimax: Efficient Baselines for Autocurricula in JAX. - Minqi Jiang; Michael Dennis 001; Edward Grefenstette; Tim Rocktäschel (CoRR, 2023)

Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. - Edward Hughes 001; Michael D. Dennis; Jack Parker-Holder; Feryal M. P. Behbahani; Aditi Mavalankar; Yuge Shi; Tom Schaul; Tim Rocktäschel (ICML, 2024)

Refining Minimax Regret for Unsupervised Environment Design. - Michael Beukman; Samuel Coward; Michael T. Matthews; Mattie Fellows; Minqi Jiang; Michael D. Dennis; Jakob Nicolaus Foerster (ICML, 2024)

Genie: Generative Interactive Environments. - Jake Bruce; Michael D. Dennis; Ashley Edwards; Jack Parker-Holder; Yuge Shi; Edward Hughes 001; Matthew Lai; Aditi Mavalankar; Richie Steigerwald; Chris Apps; Yusuf Aytar; Sarah Bechtle; et al. (ICML, 2024)

Open-Endedness is Essential for Artificial Superhuman Intelligence. - Edward Hughes 001; Michael Dennis 001; Jack Parker-Holder; Feryal M. P. Behbahani; Aditi Mavalankar; Yuge Shi; Tom Schaul; Tim Rocktäschel (CoRR, 2024)

BAMDP Shaping: a Unified Theoretical Framework for Intrinsic Motivation and Reward Shaping. - Aly Lidayan; Michael Dennis 001; Stuart Russell 001 (CoRR, 2024)

BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping. - Aly Lidayan; Michael D. Dennis; Stuart Russell 001 (ICLR, 2025)

Multi-Agent Risks from Advanced AI. - Lewis Hammond; Alan Chan; Jesse Clifton; Jason Hoelscher-Obermaier; Akbir Khan; Euan McLean; Chandler Smith; Wolfram Barfuss; Jakob N. Foerster; Tomas Gavenciak; The Anh Han; Edward Hughes 001; et al. (CoRR, 2025)

Mitigating Goal Misgeneralization via Minimax Regret. - Karim Abdel Sadek; Matthew Farrugia-Roberts; Usman Anwar; Hannah Erlebach; Christian A. Schröder de Witt; David Krueger 001; Michael Dennis 001 (CoRR, 2025)