Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

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

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

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"

A reinforcement learning package for Julia

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

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

Deep Q-learning for playing flappy bird game

Deep Q-learning for playing tetris game

Implementations of Reinforcement Learning Models in Tensorflow

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

RAD: Reinforcement Learning with Augmented Data

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.

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

A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.

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

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

A collection of various RL algorithms like policy gradients, DQN and PPO. The goal of this repo will be to make it a go-to resource for learning about RL. How to visualize, debug and solve RL problems. I've additionally included playground.py for learning more about OpenAI gym, etc.

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

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

"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer

Deep Reinforcement Learning For Trading

Reinforcement learning (RL) implementation of imperfect information game Mahjong using markov decision processes to predict future game states

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