Reinforcement Learning(RL) is a branch of Machine Learning that idealizes learning methods like Humans.It has evovled overtime and thus each learning algorithm has its own flavour.One needs to know which algorithm is most suitable to a given problem.Thus analysing RL methods becomes crucial.

This repository contains most of the RL algorithms applied in a sample environment or through a simple problem. Many of the problems have been based on the book "Reinforcement Learning:An Introduction by Sutton and Barto".

To make this repository more user friendly and informative,I have tried my best to explain each problem and thus show its result in the documentation.Even if one goes through the readme files, he or she will get a good idea of what this repository is all about!