David Silver

Research interests

Publications

• Mastering Atari, Go, chess and shogi by planning with a learned model

  RePEc: Research Papers in Economics ·

• Deep learning, reinforcement learning, and world models

  Neural Networks · 2022 · https://doi.org/10.1016/j.neunet.2022.03.037

• Applying and improving AlphaFold at CASP14

  Proteins Structure Function and Bioinformatics · 2021 · https://doi.org/10.1002/prot.26257

• Highly accurate protein structure prediction with AlphaFold

  Nature · 2021 · https://doi.org/10.1038/s41586-021-03819-2

• Improved protein structure prediction using potentials from deep learning

  Nature · 2020 · https://doi.org/10.1038/s41586-019-1923-7

• Human-level performance in 3D multiplayer games with population-based reinforcement learning

  Science · 2019 · https://doi.org/10.1126/science.aau6249

• Grandmaster level in StarCraft II using multi-agent reinforcement learning

  Nature · 2019 · 10.1038/s41586-019-1724-z

• Rainbow: Combining Improvements in Deep Reinforcement Learning

  Proceedings of the AAAI Conference on Artificial Intelligence · 2018 · 10.1609/aaai.v32i1.11796

• A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

  Science · 2018 · 10.1126/science.aar6404

• Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

  arXiv (Cornell University) · 2017 · 10.48550/arxiv.1712.01815

• Mastering the game of Go without human knowledge

  Nature · 2017 · https://doi.org/10.1038/nature24270

• StarCraft II: A New Challenge for Reinforcement Learning

  arXiv (Cornell University) · 2017 · https://doi.org/10.48550/arxiv.1708.04782

• Emergence of Locomotion Behaviours in Rich Environments

  arXiv (Cornell University) · 2017 · https://doi.org/10.48550/arxiv.1707.02286

• Mastering the game of Go with deep neural networks and tree search

  Nature · 2016 · https://doi.org/10.1038/nature16961

• Deep Reinforcement Learning with Double Q-Learning

  Proceedings of the AAAI Conference on Artificial Intelligence · 2016 · 10.1609/aaai.v30i1.10295

• Continuous control with deep reinforcement learning

  arXiv (Cornell University) · 2016

• Asynchronous Methods for Deep Reinforcement Learning

  arXiv (Cornell University) · 2016 · 10.48550/arxiv.1602.01783

• Deep Reinforcement Learning with Double Q-Learning

  AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI)) · 2016 · 10.1609/aaai.v30i1.10295

• Prioritized Experience Replay

  arXiv (Cornell University) · 2015 · 10.48550/arxiv.1511.05952

• Human-level control through deep reinforcement learning

  Nature · 2015 · https://doi.org/10.1038/nature14236

• Universal Value Function Approximators

  Journal · 2015

• Deterministic Policy Gradient Algorithms

  HAL (Le Centre pour la Communication Scientifique Directe) · 2014

• Playing Atari with Deep Reinforcement Learning

  arXiv (Cornell University) · 2013 · 10.48550/arxiv.1312.5602

• Monte-Carlo Planning in Large POMDPs

  DSpace@MIT (Massachusetts Institute of Technology) · 2010

• Cooperative Pathfinding

  Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · 2005 · https://doi.org/10.1609/aiide.v1i1.18726

Current projects

No projects listed.