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reinforcement-learning

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jackgerrits
jackgerrits commented Dec 1, 2021

../build/vowpalwabbit/vw --marginal f --noconstant --initial_numerator 0.5 --initial_denominator 1.0 --decay 0.001 --readable_model readable_model.txt

Data:

0.5 |m constant id1
1.0 |m constant id2
0.25 |m constant id3
0.4 |m constant id1

Observed invert hash model:

Version 8.11.0
Id 
Min label:0
Max label:1
bits:18
lda:0
0 ngram:
0 skip:
options: --marginal m
C
annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  • Updated Dec 14, 2021
  • Jupyter Notebook
stable-baselines
calerc
calerc commented Nov 23, 2020

The following applies to DDPG and TD3, and possibly other models. The following libraries were installed in a virtual environment:

numpy==1.16.4
stable-baselines==2.10.0
gym==0.14.0
tensorflow==1.14.0

Episode rewards do not seem to be updated in model.learn() before callback.on_step(). Depending on which callback.locals variable is used, this means that:

  • episode rewards may n

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