Methods › Reinforcement Learning › Randomized Value Functions › Noisy Linear Layer
Noisy Linear Layer
Introduced by Meire Fortunato et al. in Noisy Networks for Exploration
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
A Noisy Linear Layer is a linear layer with parametric noise added to the weights. This induced stochasticity can be used in reinforcement learning networks for the agent's policy to aid efficient exploration. The parameters of the noise are learned with gradient descent along with any other remaining network weights. Factorized Gaussian noise is the type of noise usually employed.
The noisy linear layer takes the form:
y = (b + Wx) + (b_(noisy)⊙ϵᵇ+(W_(noisy)⊙ϵʷ)x)
where ϵᵇ and ϵʷ are random variables.
Papers archive 2025-07-28
11 shown of 11, 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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Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC 6 Nov 2024 · 3 repositories · arXiv:2411.03820Syntology ran 13 of 25 samples · 12 unverified · 21 pointer-only (licence)
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Reducing Variance in Temporal-Difference Value Estimation via Ensemble of Deep Networks 16 Sep 2022 · 1 repository · arXiv:2209.07670
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DNA: Proximal Policy Optimization with a Dual Network Architecture 20 Jun 2022 · 1 repository · arXiv:2206.10027
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Deep Reinforcement Learning at the Edge of the Statistical Precipice 30 Aug 2021 · 3 repositories · arXiv:2108.13264Syntology ran 5 of 5 samples · 0 unverified
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Weighted Bellman Backups for Improved Signal-to-Noise in Q-Updates 1 Jan 2021 · 0 repositories
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A New Approach for Tactical Decision Making in Lane Changing: Sample Efficient Deep Q Learning with a Safety Feedback Reward 24 Sep 2020 · 0 repositories · arXiv:2009.11905
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SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning 9 Jul 2020 · 1 repository · arXiv:2007.04938
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NROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration 19 Jun 2020 · 0 repositories · arXiv:2006.10980
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Generative Adversarial Imagination for Sample Efficient Deep Reinforcement Learning 30 Apr 2019 · 0 repositories · arXiv:1904.13255
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Rainbow: Combining Improvements in Deep Reinforcement Learning 6 Oct 2017 · 34 repositories · arXiv:1710.02298Syntology ran 2 of 6 samples · 4 unverified · 1 pointer-only (licence)
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Noisy Networks for Exploration 30 Jun 2017 · 15 repositories · arXiv:1706.10295Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
Tasks archive 2025-07-28
13 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
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Categories archive 2025-07-28
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