Methods › Reinforcement Learning › Replay Memory › Prioritized Experience Replay › Papers where code ran, page 1
Prioritized Experience Replay
Papers archive 2025-07-28
archive papers tagged: 138 · with a code link: 61 · where Syntology ran a sample: 19 (17 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (19 of 138 tagged: 17 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument)
Syntology We ran code from the paper's repository; we did not isolate this method inside it.
Page 1 of 1: papers 1 to 19 of the 19 tagged papers where Syntology ran at least one harvested sample (17 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument), newest first by the archive's date (ties by arXiv id). This is a filter on Syntology's record ordered by date only, not a ranking; a run is not a correctness claim. A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.
Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.
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OptionZero: Planning with Learned Options 23 Feb 2025 · 1 repository · arXiv:2502.16634Syntology official (archive's flag): 7 ran · 7 ran (of which 7 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 7 samples that ran constructed an object rather than computing a result (of 8 harvested samples) · 8 pointer-only (licence)
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Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC 6 Nov 2024 · 3 repositories · arXiv:2411.03820Syntology official (archive's flag): 3 ran · 16 ran (of which 10 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 3 where Syntology's instrument failed) · 9 unverified (of 25 harvested samples) · 21 pointer-only (licence)
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MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games 17 Oct 2023 · 1 repository · arXiv:2310.11305Syntology official (archive's flag): 6 ran · 6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 7 harvested samples)
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AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning 7 Aug 2023 · 1 repository · arXiv:2308.03526Syntology 4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples)
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Decoupled Prioritized Resampling for Offline RL 8 Jun 2023 · 2 repositories · arXiv:2306.05412Syntology official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample)
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Human-level Atari 200x faster 15 Sep 2022 · 1 repository · arXiv:2209.07550Syntology 1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified (of 3 harvested samples)
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Transformers are Sample-Efficient World Models 1 Sep 2022 · 2 repositories · arXiv:2209.00588Syntology official (archive's flag): 17 ran · 17 ran (of which 13 constructed an object rather than computing a result; 16 with no instrument failure: 1 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 9 unverified (of 26 harvested samples) · 26 pointer-only (licence)
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Mastering Atari Games with Limited Data 30 Oct 2021 · 3 repositories · arXiv:2111.00210Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
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Large Batch Experience Replay 4 Oct 2021 · 2 repositories · arXiv:2110.01528Syntology official (archive's flag): 5 ran · 7 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified (of 11 harvested samples)
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Deep Reinforcement Learning at the Edge of the Statistical Precipice 30 Aug 2021 · 3 repositories · arXiv:2108.13264Syntology official (archive's flag): 5 ran · 5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 4 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples)
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Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarking 15 Nov 2020 · 1 repository · arXiv:2011.07537Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified (of 4 harvested samples)
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The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning 7 Jul 2020 · 2 repositories · arXiv:2007.03158Syntology official (archive's flag): 1 ran · 1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; the one sample that ran constructed an object rather than computing a result (of 2 harvested samples)
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Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model 19 Nov 2019 · 18 repositories · arXiv:1911.08265Syntology 43 ran (of which 36 constructed an object rather than computing a result; 43 with no instrument failure: 4 honoured, 0 violated, 39 with no contract checked; 0 where Syntology's instrument failed) · 21 unverified (of 64 harvested samples) · 62 pointer-only (licence)
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Google Research Football: A Novel Reinforcement Learning Environment 25 Jul 2019 · 1 repository · arXiv:1907.11180Syntology official (archive's flag): 4 ran · 4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 4 harvested samples)
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TF-Replicator: Distributed Machine Learning for Researchers 1 Feb 2019 · 1 repository · arXiv:1902.00465Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
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An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution 9 Jul 2018 · 24 repositories · arXiv:1807.03247Syntology community repositories only · 5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples)
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Distributed Prioritized Experience Replay 2 Mar 2018 · 15 repositories · arXiv:1803.00933Syntology 9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 6 unverified (of 15 harvested samples) · 3 pointer-only (licence)
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Rainbow: Combining Improvements in Deep Reinforcement Learning 6 Oct 2017 · 34 repositories · arXiv:1710.02298Syntology 5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 1 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified (of 6 harvested samples) · 1 pointer-only (licence)
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Prioritized Experience Replay 18 Nov 2015 · 77 repositories · arXiv:1511.05952Syntology 80 ran (of which 62 constructed an object rather than computing a result; 72 with no instrument failure: 4 honoured, 0 violated, 68 with no contract checked; 8 where Syntology's instrument failed) · 31 unverified (of 111 harvested samples) · 43 pointer-only (licence)