StarCraft II: A New Challenge for Reinforcement Learning. - Oriol Vinyals; Timo Ewalds; Sergey Bartunov; Petko Georgiev; Alexander Sasha Vezhnevets; Michelle Yeo; Alireza Makhzani; Heinrich Küttler; John P. Agapiou; Julian Schrittwieser; John Quan; Stephen Gaffney; et al. (CoRR, 2017)

OpenSpiel: A Framework for Reinforcement Learning in Games. - Marc Lanctot; Edward Lockhart; Jean-Baptiste Lespiau; Vinícius Flores Zambaldi; Satyaki Upadhyay; Julien Pérolat; Sriram Srinivasan 005; Finbarr Timbers; Karl Tuyls; Shayegan Omidshafiei; Daniel Hennes; Dustin Morrill; et al. (CoRR, 2019)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Improving alignment of dialogue agents via targeted human judgements. - Amelia Glaese; Nat McAleese; Maja Trebacz; John Aslanides; Vlad Firoiu; Timo Ewalds; Maribeth Rauh; Laura Weidinger; Martin J. Chadwick; Phoebe Thacker; Lucy Campbell-Gillingham; Jonathan Uesato; et al. (CoRR, 2022)

GraphCast: Learning skillful medium-range global weather forecasting. - Rémi Lam; Alvaro Sanchez-Gonzalez; Matthew Willson; Peter Wirnsberger; Meire Fortunato; Alexander Pritzel; Suman V. Ravuri; Timo Ewalds; Ferran Alet; Zach Eaton-Rosen; Weihua Hu; Alexander Merose; et al. (CoRR, 2022)

Magnetic control of tokamak plasmas through deep reinforcement learning. - Jonas Degrave; Federico Felici; Jonas Buchli; Michael Neunert; Brendan D. Tracey; Francesco Carpanese; Timo Ewalds; Roland Hafner; Abbas Abdolmaleki; Diego de Las Casas; Craig Donner; Leslie Fritz; et al. (Nat., 2022)

Towards practical reinforcement learning for tokamak magnetic control. - Brendan D. Tracey; Andrea Michi; Yuri Chervonyi; Ian Davies; Cosmin Paduraru; Nevena Lazic; Federico Felici; Timo Ewalds; Craig Donner; Cristian Galperti; Jonas Buchli; Michael Neunert; et al. (CoRR, 2023)

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. - Michaël Mathieu; Sherjil Ozair; Srivatsan Srinivasan; Çaglar Gülçehre; Shangtong Zhang; Ray Jiang; Tom Le Paine; Richard Powell; Konrad Zolna; Julian Schrittwieser; David H. Choi; Petko Georgiev; et al. (CoRR, 2023)

GenCast: Diffusion-based ensemble forecasting for medium-range weather. - Ilan Price; Alvaro Sanchez-Gonzalez; Ferran Alet; Timo Ewalds; Andrew El-Kadi; Jacklynn Stott; Shakir Mohamed; Peter W. Battaglia; Rémi Lam; Matthew Willson (CoRR, 2023)

Probabilistic weather forecasting with machine learning. - Ilan Price; Alvaro Sanchez-Gonzalez; Ferran Alet; Tom R. Andersson; Andrew El-Kadi; Dominic Masters; Timo Ewalds; Jacklynn Stott; Shakir Mohamed; Peter W. Battaglia; Rémi R. Lam; Matthew Willson (Nat., 2025)