Deep Reinforcement Learning with TensorFlow 2.1
Source code accompanying the blog post Deep Reinforcement Learning with TensorFlow 2.1.
In the blog post, I showcase the
TensorFlow 2.1 features through the lens of deep reinforcement learning
by implementing an advantage actor-critic agent, solving the classic
While the goal is to showcase
TensorFlow 2.1, I also provide a brief overview of the DRL methods.
To run it locally, install the dependencies with
pip install -r requirements.txt, and then execute
To control various hyperparameters, specify them as flags, e.g.
python a2c.py --batch_size=256.