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Project : Reinforcement Learning

Train a Smartcab How to Drive

Install

This project requires Python 2.7 with the pygame library installed

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.

O/P for the given code

https://cloud.githubusercontent.com/assets/9404205/22600219/9b7ac07e-ea5f-11e6-981d-2fd6529a9e87.png https://cloud.githubusercontent.com/assets/9404205/22600241/ac4411c6-ea5f-11e6-936b-ed0feec81a5a.png https://cloud.githubusercontent.com/assets/9404205/22600263/c28de646-ea5f-11e6-9679-4e6fc5707a42.png https://cloud.githubusercontent.com/assets/9404205/22600271/ca2f65e6-ea5f-11e6-8a5f-a43356ff911a.png https://cloud.githubusercontent.com/assets/9404205/22600278/d13b5002-ea5f-11e6-997e-a93be61f1989.png

About

In this, the self-driving agent uses RL techniques in a simplified world (created using Pygame) to effectively reaching its destinations in the allotted time. It uses Q-Learning algorithm to find the best configuration of learning and exploration factors to ensure that it is reaching its destinations with consistently positive results without caus…

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