Reinforcement-Learning-Stamatics

This repository provides code, exercises and solutions for popular Reinforcement Learning algorithms which I learned during my Stamatics project . I finally implemented Pong and breakout Atari games using DQN algorithms . Implementations of these using Double-DQN and A3C algorithms would be pushed soon . These are meant to serve as a learning tool to complement the theoretical materials from:-

• Reinforcement Learning: An Introduction (2nd Edition)
• David Silver's Reinforcement Learning Course

Each folder in corresponds to one or more chapters of the above textbook and/or course. In addition to exercises and solution, each folder also contains a list of learning goals, a brief concept summary, and links to the relevant readings.

All code is written in Python 3 and uses RL environments from OpenAI Gym. Advanced techniques use Pytorch for neural network implementations.

Resources

Textbooks:

• Reinforcement Learning: An Introduction (2nd Edition)

Classes:

• David Silver's Reinforcement Learning Course (UCL, 2015)
• CS294 - Deep Reinforcement Learning (Berkeley, Fall 2015)