Using Q-learning on a discretised version of the cart pole problem as a basic reinforcement learning implementation. In the second rendition, I use a NN to predict Q-values on the continuous state-space (deep reinforcement learning).
Install requirements.txt:
cd
into root directory and run:
pip install -r requirements.txt
once all requirements are installed run
python3 deep_q_learning.py
for the deep q-learning version
python3 discrete_q_learning.py
for the discretised q-learning version
Because training is an inherently statistical process, results may vary and you may need to re-run the simulations a couple of times before you get optimal results.