agravier/rl-experiments

Reinforcement learning notes, snippets and experiments

rl-experiments

Reinforcement learning notes, snippets and experiments.

I usually read Barto and Tutton's RL book when I'm in public transport or in other occasions when I don't have my computer, so I implement things in Python on my phone. I sometimes work on it on my computer too.

So this codebase is a little strange because of the limitations of my development environment on my phone (an Android app called pydroid 3, a markdown editor and a git client).

Installing

You need Python 3.6 or higher. Here I assume Python 3.7.2, installed on a *nix platform pyenv. The libraries used are listed in the requirements file, but some that are related to visualization are platform dependent and not listed in the requirements file.

pyenv install 3.7.2
pyenv virtualenv 3.7.2 rl-experiments
pyenv activate rl-experiments
pip install -r requirements.txt

Before running anything, remember to activate the virtualenv:

pyenv activate rl-experiments

Testing

For practical reasons (implementing on the phone), all software tests are defined and run in the tests.py file.

python tests.py

Running without GUI

The main.py below changes often as I go through the book and experiment with different things, I'll eventually make something more organized, maybe following the book's ToC. OR allowing to combine any compatible learner with any RL problem.

python main.py

Graphical user interface

I mostly try to get the kivy UI to work on android. I'm not sure if it does anything sensible on a computer.

The kivy UI uses matplotlib to graph various parameters. Matplotlib integrates with kivy as follows:

• on a computer: garden install matplotlib
• on Android with pydroid 3: Use the quick install menu to install kivymatplot.

I am currently trying out some approaches in kivy_mpl_test.py.