Methods › Reinforcement Learning › Distributed Reinforcement Learning › TorchBeast
TorchBeast
Introduced by Heinrich Küttler et al. in TorchBeast: A PyTorch Platform for Distributed RL
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
TorchBeast is a platform for reinforcement learning (RL) research in PyTorch. It implements a version of the popular IMPALA algorithm for fast, asynchronous, parallel training of RL agents.
Papers archive 2025-07-28
2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform 29 Sep 2023 · 1 repository · arXiv:2310.00036Syntology ran 4 of 8 samples · 4 unverified · 8 pointer-only (licence)
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TorchBeast: A PyTorch Platform for Distributed RL 8 Oct 2019 · 3 repositories · arXiv:1910.03552Syntology ran 4 of 9 samples · 5 unverified · 3 pointer-only (licence)
Tasks archive 2025-07-28
5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Reinforcement Learning | 2 |
| Deep Reinforcement Learning | 1 |
| OpenAI Gym | 1 |
| Reinforcement Learning (RL) | 1 |
| reinforcement-learning | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections