← Back to project summary Q-Learning Gridworlds
A closer look at the app, the systems I owned, and the features behind it.
What is in the repo
- Environment setup for Taxi and for Frozen Lake in both deterministic and slippery variants, with the time limit wrapper rewrapped so episode length is controlled explicitly.
- An epsilon-greedy training loop and a separate greedy evaluation loop that reports average discounted reward.
- Debugging aids that print the learned policy as a readable grid.
- Experiment sweeps with pandas and Plotly for charting learning rate and epsilon.
What is missing
- The QValues data structure, the Q-learning update rule, the value lookup, and best-action selection are all left as TODO.
- Listed here for completeness, and because the harness around it is a reasonable piece of work on its own.