A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
David Silver, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, Laurent Sifre, Dharshan Kumaran, Thore Graepel, Timothy Lillicrap, Karen Simonyan, Demis Hassabis
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Citation edge evidence
- Grandmaster level in StarCraft II using multi-agent reinforcement learning→A general reinforcement learning algorithm that masters chess, shogi, and Go through self…Legacy edge — source detail unavailable
- A continual learning survey: Defying forgetting in classification tasks→A general reinforcement learning algorithm that masters chess, shogi, and Go through self…Legacy edge — source detail unavailable
- A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development→A general reinforcement learning algorithm that masters chess, shogi, and Go through self…Legacy edge — source detail unavailable
- Mastering Atari, Go, chess and shogi by planning with a learned model→A general reinforcement learning algorithm that masters chess, shogi, and Go through self…Legacy edge — source detail unavailable
- A general reinforcement learning algorithm that masters chess, shogi, and Go through self…→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
- A general reinforcement learning algorithm that masters chess, shogi, and Go through self…→Mastering the game of Go without human knowledgeLegacy edge — source detail unavailable
- Mastering the game of Go without human knowledge→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
- Grandmaster level in StarCraft II using multi-agent reinforcement learning→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
- Mastering Atari, Go, chess and shogi by planning with a learned model→Mastering the game of Go with deep neural networks and tree searchLegacy edge — source detail unavailable
- Mastering Atari, Go, chess and shogi by planning with a learned model→Mastering the game of Go without human knowledgeLegacy edge — source detail unavailable
- Mastering Atari, Go, chess and shogi by planning with a learned model→Grandmaster level in StarCraft II using multi-agent reinforcement learningLegacy edge — source detail unavailable
- A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development→Grandmaster level in StarCraft II using multi-agent reinforcement learningLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Mastering the game of Go with deep neural networks and tree search | 2016 | 16,014 |
| Mastering the game of Go without human knowledge | 2017 | 9,313 |
What cites it, inside the corpus
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Topics
| Artificial Intelligence in Games | Computer Science |
| Reinforcement Learning in Robotics | Computer Science |
| Evolutionary Algorithms and Applications | Computer Science |
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