Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Related tags

Deep Learning reinforcement-learning pytorch qr-dqn quantile-regression-dqn
Overview

Quantile Regression DQN

Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arxiv.org/abs/1710.10044).

Open In Colab

Requirements (Python 3.6)

pip3 install gym, torch, numpy, tabulate, pandas

Credits

Joint work with Mikhail Konobeev. Of course, do not forget to cite Distributional Reinforcement Learning with Quantile Regression (https://arxiv.org/abs/1710.10044).

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Comments
  • loss calculation

    loss calculation

    Hello.

    I have noticed that when loss is calculated there is detach() statement on diff:

    loss = huber(diff) * (tau - (diff.detach() < 0).float()).abs()

    could you please explain the reason?

    Thanks a lot.

    opened by merv22 4
  • Running error

    Running error

    Firstly, I run the rl_utils.py and it generate a qr-dqn-solution-cool.ipynb file. When I try to run the code in ipython notebook, the following error occured. Is there something wrong?

    self.print = prin
         ^

    SyntaxError: invalid syntax

    opened by PygmalionChen 1
  • Visualization part

    Visualization part

    Hi, would you like to share the code for the img you used in gif format for each steps. It's a cool work, I would like to learn this, can you please share the code if possible.

    opened by jahidhasanlinix 2
Owner
Arsenii Senya Ashukha
Research scientist at @SamsungLabs AI Center Moscow @bayesgroup
Arsenii Senya Ashukha
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