Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. - David Silver; Thomas Hubert; Julian Schrittwieser; Ioannis Antonoglou; Matthew Lai; Arthur Guez; Marc Lanctot; Laurent Sifre; Dharshan Kumaran; Thore Graepel; Timothy P. Lillicrap; Karen Simonyan; et al. (CoRR, 2017)

Mastering the game of Go without human knowledge. - David Silver; Julian Schrittwieser; Karen Simonyan; Ioannis Antonoglou; Aja Huang; Arthur Guez; Thomas Hubert; Lucas Baker; Matthew Lai; Adrian Bolton; Yutian Chen 001; Timothy P. Lillicrap; et al. (Nat., 2017)

Monte-Carlo Tree Search as Regularized Policy Optimization. - Jean-Bastien Grill; Florent Altché; Yunhao Tang; Thomas Hubert; Michal Valko; Ioannis Antonoglou; Rémi Munos (ICML, 2020)

Mastering Atari, Go, chess and shogi by planning with a learned model. - Julian Schrittwieser; Ioannis Antonoglou; Thomas Hubert; Karen Simonyan; Laurent Sifre; Simon Schmitt; Arthur Guez; Edward Lockhart; Demis Hassabis; Thore Graepel; Timothy P. Lillicrap; David Silver (Nat., 2020)

Learning and Planning in Complex Action Spaces. - Thomas Hubert; Julian Schrittwieser; Ioannis Antonoglou; Mohammadamin Barekatain; Simon Schmitt; David Silver (ICML, 2021)

Online and Offline Reinforcement Learning by Planning with a Learned Model. - Julian Schrittwieser; Thomas Hubert; Amol Mandhane; Mohammadamin Barekatain; Ioannis Antonoglou; David Silver (NeurIPS, 2021)

Planning in Stochastic Environments with a Learned Model. - Ioannis Antonoglou; Julian Schrittwieser; Sherjil Ozair; Thomas K. Hubert; David Silver (ICLR, 2022)

Approximate Exploitability: Learning a Best Response. - Finbarr Timbers; Nolan Bard; Edward Lockhart; Marc Lanctot; Martin Schmid; Neil Burch; Julian Schrittwieser; Thomas Hubert; Michael Bowling (IJCAI, 2022)

MuZero with Self-competition for Rate Control in VP9 Video Compression. - Amol Mandhane; Anton Zhernov; Maribeth Rauh; Chenjie Gu; Miaosen Wang; Flora Xue; Wendy Shang; Derek Pang; Rene Claus; Ching-Han Chiang; Cheng Chen; Jingning Han; et al. (CoRR, 2022)

Competition-Level Code Generation with AlphaCode. - Yujia Li 001; David H. Choi; Junyoung Chung; Nate Kushman; Julian Schrittwieser; Rémi Leblond; Tom Eccles; James Keeling; Felix Gimeno; Agustin Dal Lago; Thomas Hubert; Peter Choy; et al. (CoRR, 2022)

Discovering faster matrix multiplication algorithms with reinforcement learning. - Alhussein Fawzi; Matej Balog; Aja Huang; Thomas Hubert; Bernardino Romera-Paredes; Mohammadamin Barekatain; Alexander Novikov 001; Francisco J. R. Ruiz; Julian Schrittwieser; Grzegorz Swirszcz; David Silver; Demis Hassabis; et al. (Nat., 2022)

Optimizing Memory Mapping Using Deep Reinforcement Learning. - Pengming Wang 001; Mikita Sazanovich; Berkin Ilbeyi; Phitchaya Mangpo Phothilimthana; Manish Purohit; Han Yang Tay; Ngân Vu; Miaosen Wang; Cosmin Paduraru; Edouard Leurent; Anton Zhernov; Julian Schrittwieser; et al. (CoRR, 2023)

Faster sorting algorithms discovered using deep reinforcement learning. - Daniel J. Mankowitz; Andrea Michi; Anton Zhernov; Marco Gelmi; Marco Selvi; Cosmin Paduraru; Edouard Leurent; Shariq Iqbal; Jean-Baptiste Lespiau; Alex Ahern; Thomas Köppe; Kevin Millikin; et al. (Nat., 2023)