The smartcab project was done as part of Udacity's Machine Learning Engineer Nanodegree. This README file describes the coding infrastructure and how to install the initial coding templates.
Additional project description can be found on the project_description.md file inside this repository.
Individual contribution to the project was done in the smartcab.ipynb Jupyter Notebook file, which was converted to html as well (report.html file).
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.
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.