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Udacity Nanodegree Project 4: Example of reinforcement learning. Training a Smartcab to drive on a rectangular grid.

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Project 4: Reinforcement Learning

Train a Smartcab How to Drive

Install

This project requires Python 2.7 with the pygame library installed

Code

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.

Run

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.

UdacityND_Smartcab

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Udacity Nanodegree Project 4: Example of reinforcement learning. Training a Smartcab to drive on a rectangular grid.

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