Simple Reinforcement learning tutorials

Tensorflow tutorial from basic to hard

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

Minimal and Clean Reinforcement Learning Examples

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

Deep Reinforcement Learning based Trading Agent for Bitcoin

Implementations of Reinforcement Learning Models in Tensorflow

Deep Q-learning for playing flappy bird game

Deep Q-learning for playing tetris game

CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning

Deep Q-Learning Network in pytorch (not actively maintained)

RAD: Reinforcement Learning with Augmented Data

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Trained A Convolutional Neural Network To Play 2048 using Deep-Reinforcement Learning

A reinforcement learning package for Julia

Forex trading simulator environment for OpenAI Gym, observations contain the order status, performance and timeseries loaded from a CSV file containing rates and indicators. Work In Progress

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

Pytorch implementation of distributed deep reinforcement learning

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

A simple example of how to implement vector based DQN using PyTorch and a ML-Agents environment

Deep Reinforcement Learning For Trading

Swift port of ConvnetJS. [Work in progress]