yanndupis / smartcab

Reinforcement learning techniques for a self-driving agent

Reinforcement Learning

Project: Train a Smartcab How to Drive

Project Overview

In this project we will apply reinforcement learning techniques for a self-driving agent in a simplified world to aid it in effectively reaching its destinations in the allotted time.

Install

This project requires Python 2.7 with the pygame library installed

Code

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.

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.