Methods › General › Regularization › Entropy Regularization

Entropy Regularization

1,128 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Entropy Regularization is a type of regularization used in reinforcement learning. For on-policy policy gradient based methods like A3C, the same mutual reinforcement behaviour leads to a highly-peaked π(a|s) towards a few actions or action sequences, since it is easier for the actor and critic to overoptimise to a small portion of the environment. To reduce this problem, entropy regularization adds an entropy term to the loss to promote action diversity:

H(X) = -∑π(x)log(π(x))

Image Credit: Wikipedia

Source: Asynchronous Methods for Deep Reinforcement LearningSee Code · ikostrikov/pytorch-a3c

Papers archive 2025-07-28

30 shown of 1,128, 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.

Tasks archive 2025-07-28

20 shown of 404 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Reinforcement Learning (RL)376
reinforcement-learning328
Reinforcement Learning301
Autonomous Driving248
Deep Reinforcement Learning183
Autonomous Vehicles80
Decision Making70
Imitation Learning60
Object Detection54
object-detection50
Continuous Control47
MuJoCo44
continuous-control43
Semantic Segmentation40
Q-Learning38
Language Modelling34
Atari Games31
Multi-agent Reinforcement Learning30
OpenAI Gym26
Language Modeling25

Usage over time archive 2025-07-28

Papers per year tagged with Entropy Regularization: 2016 to 2025, peak 260 260 0 2016: 4 papers 2016 2017: 17 papers 2017 2018: 34 papers 2018 2019: 72 papers 2019 2020: 123 papers 2020 2021: 133 papers 2021 2022: 168 papers 2022 2023: 174 papers 2023 2024: 260 papers 2024 2025: 143 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (1,128 dated). Bars are counts, not a trend claim.

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

Regularization

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