Project submission by Edward Minnett (ed@methodic.io).

August 2nd 2016. (Revision 1)

This project requires Python 2.7 with the pygame library installed

Template code is provided in the smartcab/agent.py python file. Additional supporting python code can be found in smartcab/enviroment.py, smartcab/planner.py, and smartcab/simulator.py. Supporting images for the graphical user interface can be found in the images folder. While some code has already been implemented to get you started, you will need to implement additional functionality for the LearningAgent class in agent.py when requested to successfully complete the project.

Udacity has a hard limit on GitHub project submissions that prevents submitting a repository with more than 1000 files. The grid search generated 1024 files as a result, the gridSearch results have not all been committed to the repository. However, the results for alphas 0.01, 0.5, and 0.7 remain in the repository as they contain the optimal result and are required to execute the IPython notebook.

In a terminal or command window, navigate to the top-level project directory smartcab/ (that contains this README) and run one of the following commands:

python smartcab/agent.py
python -m smartcab.agent

This will run the agent.py file and execute your agent code.

Run the following in the terminal from the project root:

$ ipython nbconvert smartcab_analysis.ipynb --to pdf
$ mv smartcab_analysis.pdf report.pdf