Implemented different RL algorithms to solve the infamous CartPole problem.

• Q-Learning:

  "Bucket-ised" the continous state space to construct a lookup table, a Q-table, which is used to perform updates as governed by the Bellman Optimality Equation. Check out q_learning_results.txt and the q_learning_plots folder for the write-up (on the complete training process) and plots, for consecutive runs, respectively.

  Insights from Ferdinand and Matthew.

• Deep Q-Networks (DQN):

  (Coming soon)

• Tuning and update q_learning_results.txt
• Implement DQN (with experience replay?)