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Deep Reinforcement Learning

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/INF554MachineLearning/GameAI

An Introduction to Deep Reinforcement Learning

https://github.com/IRLL/Atari-Data-Scraper

The Atari Data Scraper

https://github.com/IlyaGusev/summarus

Deep Reinforcement Learning For Sequence to Sequence Models

https://github.com/Improbable-AI/curiosity_baselines

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

https://github.com/InSpaceAI/RL-Zoo

Playing Atari with Deep Reinforcement Learning

https://github.com/Ipsedo/EvoMotion

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/Ishan-Kumar2/Reinforcement-Learning-on-2048

Playing Atari with Deep Reinforcement Learning

https://github.com/IvanVigor/Deep-Deterministic-Policy-Gradient-Unity-Env

Continuous control with deep reinforcement learning

https://github.com/IvanVigor/MADDPG-Unity

Continuous control with deep reinforcement learning

https://github.com/Ivsxk/RAT

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/J93T/TP4-DDPG

Continuous control with deep reinforcement learning

https://github.com/JBGUIMBAUD/deep-reenforcement-learning

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/JBLanier/distributed-rl-for-imperfect-info-games

Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games

https://github.com/JIElite/AI-research-papers

Deep Reinforcement Learning for Playing 2.5D Fighting Games

https://github.com/JL321/mujo-2DHalf-Cheetah

Continuous control with deep reinforcement learning

https://github.com/JL321/mujo-2DWalker

Continuous control with deep reinforcement learning

https://github.com/JackFurby/Breakout

Playing Atari with Deep Reinforcement Learning

https://github.com/JacopoPan/gym-pybullet-drones

Flightmare: A Flexible Quadrotor Simulator

https://github.com/JanghoonChoi/janghoonchoi.github.io

Real-time visual tracking by deep reinforced decision making

https://github.com/JasperBusschers/multi-objective-Rubik-s-cube

Solving the Rubik's Cube Without Human Knowledge

https://github.com/JayLohokare/banana-world-navigation

Rainbow: Combining Improvements in Deep Reinforcement Learning

https://github.com/JinTanda/MADDPG_env

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/JiqianDong/GCQ_source

A DRL-based Multiagent Cooperative Control Framework for CAV Networks: a Graphic Convolution Q Network

https://github.com/Joearrowsmith/hackcambridge_2020

Deep Recurrent Q-Learning for Partially Observable MDPs

https://github.com/JohanSamir/rainbow_extend

Revisiting Rainbow: Promoting more Insightful and Inclusive Deep Reinforcement Learning Research

https://github.com/JohannesAck/MATD3implementation

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/JohannesAck/tf2multiagentrl

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/JonasLeininger/ray-population-based-training

Population Based Training of Neural Networks

https://github.com/JonasRSV/DDPG

Continuous control with deep reinforcement learning

https://github.com/JonasRSV/DQN

Playing Atari with Deep Reinforcement Learning

https://github.com/JonasRSV/DQNTensorflow

Playing Atari with Deep Reinforcement Learning

https://github.com/JonasRSV/PGTensorflow

Continuous control with deep reinforcement learning

https://github.com/JorgeA-RD/Reinforcement-Learning-Agents/tree/main/DDPG

Continuous control with deep reinforcement learning

https://github.com/JulT1/RL_SS19

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/JuliaPOMDP/DeepQLearning.jl

Playing Atari with Deep Reinforcement Learning

https://github.com/JulienDesvergnes/human-reinforcement-learning

Deep reinforcement learning from human preferences

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