Methods › Reinforcement Learning › Reinforcement Learning Frameworks › DDQL
Double Deep Q-Learning
DDQL
Introduced by Hado van Hasselt et al. in Deep Reinforcement Learning with Double Q-learning
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
The archive carries no description for this method.
Papers archive 2025-07-28
3 shown of 3, 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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FLASH-RL: Federated Learning Addressing System and Static Heterogeneity using Reinforcement Learning 12 Nov 2023 · 1 repository · arXiv:2311.06917
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Privacy-Cost Management in Smart Meters Using Deep Reinforcement Learning 10 Mar 2020 · 0 repositories · arXiv:2003.04946
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Deep Reinforcement Learning with Double Q-learning 22 Sep 2015 · 97 repositories · arXiv:1509.06461Syntology ran 55 of 106 samples · 51 unverified · 57 pointer-only (licence)
Tasks archive 2025-07-28
8 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 |
|---|---|
| Deep Reinforcement Learning | 2 |
| Q-Learning | 2 |
| Reinforcement Learning | 2 |
| Reinforcement Learning (RL) | 2 |
| reinforcement-learning | 2 |
| Atari Games | 1 |
| Federated Learning | 1 |
| Management | 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