qlearning

Q-learning algorithms based on app structure


License
BSD-3-Clause
Install
pip install qlearning==1.0.0

Documentation

Tf Gym App

Build Status

Description

Small definition of a gym tensorflow app

Installation

Dependencies for that program work well

pip install gym gym[atari] tensorflow keras gym-super-mario-bros

or you can made an python environment with anaconda

conda create -n tf python=3.6 gym gym[atari] tensorflow keras gym-super-mario-bros

Basic usage with example for a pre-defined case or a suited one

python app.py

or you can build a binary

bazel build :app

After that you can execute

./bazel-bin/app

Properties available to activate as arguments

First small example

python app.py --environment_name "Gomoku19x19-v0" --render "presented" --action_type "dqn" --pre_defined_state_size "gym-gomoku"

Thinking on relations like test

python app_test.py

or just doing the same to produce a binary in another way

bazel build :app_test

For tests too, you can have an access of that binary

./bazel-bin/app_test