Deep Reinforcement Learning

Introduction

• This Repository contains multiple Projects on Reinforcement Learning. The problems and supporting documents are taken from udacity deep-reinforcment-learning-nanodegree github page udacity deep reinforcement Learning

• This repository is solely made for RL enthusiastic people to explore the works of Reinforcement learning and exploit its use cases.

Installation

All the RL algorithms are tested on Open Ai gym simulations. All simulations are done in the jupyter notebook, Anaconda.

• Installing Anaconda Anaconda installation
• Do not forget to activate a new environment before proceeding

Before proceeding, its highly recommended to install all the relevant packages in the new environment (Anaconda).

• conda create -n myenv python=3.7
• Libraries needed for installation
• conda install -c anaconda numpy
• pip install gym
• pip install pyglet
• pip install gym[box2d]
• For more information visit open ai gym installation The followings are packages that are required for working with the repository.

Working with the repository

• Each of the folders are marked with algorthm_simulation where the algorithm is the algorithm used to solve the simulation mentioned in open ai gym environment tab Open AI Gym Environment

Cheetsheet :

• You can also take help from udacity Deep Reinforcment Learning cheetsheet

Contribution

• Contribution to this repo is very much appreciated. You can also leave me feedback for any improvements.