Top 35 deep-q-network open source projects

Minimal and Clean Reinforcement Learning Examples

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

A reinforcement learning package for Julia

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

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.

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

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

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

1-step Q Learning from the paper "Asynchronous Methods for Deep Reinforcement Learning"

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

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

StarCraft II - pysc2 Deep Reinforcement Learning Examples

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

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

Deep Q-learning for playing flappy bird game

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

Deep Q-learning for playing tetris game

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

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

RAD: Reinforcement Learning with Augmented Data

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

[INACTIVE] A collection of various machine learning solver. The library is an object-oriented approach (baked with Typescript) and tries to deliver simplified interfaces that make using the algorithms pretty simple.

No description or website provided.

NeurIPS 2019: DQN(λ) = Deep Q-Network + λ-returns.

Pytorch implementation of distributed deep reinforcement learning

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

Semestral project for the subject Methods of computational inteligence @ fit.cvut.cz

Deep-Q-Network reinforcement learning algorithm applied to a simple 2d-car-racing environment

"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

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

Deep Reinforcement Learning Pong Agent, King Pong, he's the best