Methods › Reinforcement Learning › Policy Gradient Methods › DDPG › Papers where code ran, page 1
Deep Deterministic Policy Gradient
DDPG
Papers archive 2025-07-28
archive papers tagged: 218 · with a code link: 71 · where Syntology ran a sample: 14 (13 with a run with no instrument failure, 1 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (14 of 218 tagged: 13 with a run with no instrument failure, 1 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 14 of the 14 tagged papers where Syntology ran at least one harvested sample (13 with a run with no instrument failure, 1 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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Distributional Soft Actor-Critic with Three Refinements 9 Oct 2023 · 2 repositories · arXiv:2310.05858Syntology official (archive's flag): 5 ran · 5 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; 1 where Syntology's instrument failed) · 0 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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Safe Deep Reinforcement Learning for Multi-Agent Systems with Continuous Action Spaces 9 Aug 2021 · 1 repository · arXiv:2108.03952Syntology 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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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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Online Meta-Critic Learning for Off-Policy Actor-Critic Methods 11 Mar 2020 · 1 repository · arXiv:2003.05334Syntology official (archive's flag): 6 ran · 6 ran (of which 6 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) · 0 unverified; every one of the 6 samples that ran constructed an object rather than computing a result (of 6 harvested samples) · 6 pointer-only (licence)
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Reinforcement co-Learning of Deep and Spiking Neural Networks for Energy-Efficient Mapless Navigation with Neuromorphic Hardware 2 Mar 2020 · 1 repository · arXiv:2003.01157Syntology official (archive's flag): 3 ran · 3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 3 harvested samples)
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Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning 23 Jan 2020 · 4 repositories · arXiv:2001.08726Syntology official (archive's flag): 2 ran · 2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified (of 6 harvested samples)
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QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning 2 Oct 2019 · 1 repository · arXiv:1910.01055Syntology official (archive's flag): 1 ran · 1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 1 harvested sample) · 1 pointer-only (licence)
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Shapley Q-value: A Local Reward Approach to Solve Global Reward Games 11 Jul 2019 · 2 repositories · arXiv:1907.05707Syntology 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) · 2 unverified; the one sample that ran constructed an object rather than computing a result (of 3 harvested samples) · 3 pointer-only (licence)
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Off-Policy Deep Reinforcement Learning without Exploration 7 Dec 2018 · 10 repositories · arXiv:1812.02900Syntology community repositories only · 14 ran (of which 12 constructed an object rather than computing a result; 14 with no instrument failure: 1 honoured, 0 violated, 13 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified (of 14 harvested samples) · 9 pointer-only (licence)
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Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space 10 Oct 2018 · 5 repositories · arXiv:1810.06394Syntology 2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified (of 3 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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GEP-PG: Decoupling Exploration and Exploitation in Deep Reinforcement Learning Algorithms 14 Feb 2018 · 1 repository · arXiv:1802.05054Syntology official (archive's flag): 2 ran · 2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified (of 3 harvested samples) · 3 pointer-only (licence)
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Parameter Space Noise for Exploration 6 Jun 2017 · 10 repositories · arXiv:1706.01905Syntology 4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified (of 5 harvested samples) · 5 pointer-only (licence)
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Continuous control with deep reinforcement learning 9 Sep 2015 · 161 repositories · arXiv:1509.02971Syntology 163 ran (of which 126 constructed an object rather than computing a result; 152 with no instrument failure: 3 honoured, 0 violated, 149 with no contract checked; 11 where Syntology's instrument failed) · 143 unverified (of 306 harvested samples) · 163 pointer-only (licence)