#Dqn
Showing 52 of 52 repositories tagged #dqn, ranked by stars
An elegant PyTorch deep reinforcement learning library.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
Build your neural network easy and fast, 莫烦Python中文教学
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
Minimal and Clean Reinforcement Learning Examples
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
The most simple, flexible, and comprehensive OpenAI Gym trading environment (Approved by OpenAI Gym)
텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Deep Reinforcement Learning toolkit: record and replay cryptocurrency limit order book data & train a DDQN agent
Python library for Reinforcement Learning.
A scalable template for PyTorch projects, with examples in Image Segmentation, Object classification, GANs and Reinforcement Learning.
Deep Reinforcement Learning with pytorch & visdom
Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"
This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)
use AI to play some games.
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Structural implementation of RL key algorithms
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
playing idealized trading games with deep reinforcement learning
MindMaker UE4 Machine Learning Toolkit
AI research environment for the Atari 2600 games 🤖.
Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.
PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.
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.
[『텐서플로로 배우는 딥러닝』, 솔라리스, 영진닷컴, 2018] 도서의 소스코드입니다.
Explorer is a PyTorch reinforcement learning framework for exploring new ideas.
Reinforcement Learning | tensorflow implementation of DQN, Dueling DQN and Double DQN performed on Atari Breakout
Train a DQN Agent to play CarRacing 2d using TensorFlow and Keras.
The simplest implementation of Pensieve (SIGCOMM' 17) via state-of-the-art RL algorithms, including PPO, DQN, SAC, and support for both TensorFlow and PyTorch.
Deep Q-Learning (DQN) implementation for Atari pong.
Using reinforcement learning to train FlappyBird.
Collection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
OpenAI Gym environment solutions using Deep Reinforcement Learning.
Deep Reinforcement Learning for Fixed-Wing Flight Control with Deep Q-Network
Deep Reinforcement Learning applied to robotic arm
MIT DeepTraffic top 2% solution (75.01 mph) 🚗.
Stock price prediction and automated trading using Deep Reinforcement Learning and Machine Learning
Snake game with neural network AI model
[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.
A.I. plays the original 1980 Pacman using Neuroevolution of Augmenting Topologies and Deep Q Learning
#WORK IN PROGRESS PyTorch Implementation of Supervised and Deep Q-Learning EWC(Elastic Weight Consolidation), introduced in "Overcoming Catastrophic Forgetting in Neural Networks"
A reinforcement learing environment for robotic mobile fulfilment system (RMFS)
Learn to use reinforcement learning to maximize the profit gained from a trade.
forex trading with reinforcement learning
Algorithmic Trading Using Deep Reinforcement Learning algorithms (PPO and DQN)
NYCU Intro2AI Final Project
Applying the Trading Deep Q-Network algorithm (TDQN) on shares in the hydrogen sector.