Skip to content

Cab using reinforcement learning to learn driving in a simulation

Notifications You must be signed in to change notification settings

Kumaava/smartcab_ai

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Machine Learning Engineer Nanodegree

Reinforcement Learning

Project: 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.

This the evaluation of the final model screen shot 2017-08-23 at 3 19 15 pm

About

Cab using reinforcement learning to learn driving in a simulation

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published