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Deep Reinforcement Learning

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코드

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

https://github.com/X3N4/car_racer

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

https://github.com/XGX-CURRY/uavSim

UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach

https://github.com/XingxingZhang/dress

Sentence Simplification with Deep Reinforcement Learning

https://github.com/YYCAAA/V-MPO_Lunarlander

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

https://github.com/YanSong97/Master-thesis

Noisy Networks for Exploration

https://github.com/YangRui2015/Modular_HER

Continuous control with deep reinforcement learning

https://github.com/YaoMarkMu/DRQTRANS

Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels

https://github.com/YoUNG824/DDPG

Continuous control with deep reinforcement learning

https://github.com/YuansongFeng/MadMario

Deep Reinforcement Learning with Double Q-learning

https://github.com/YuhangSong/Mega-Reward

Deep Reinforcement Learning that Matters

https://github.com/Yutongamber/MADDPG

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

https://github.com/ZD1wang/Traffiti

An Efficient Deep Reinforcement Learning Model for Urban Traffic Control

https://github.com/ZachisGit/LearningFromHumanPreferences

Deep reinforcement learning from human preferences

https://github.com/ZainRaza14/Neuro-Evolution

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

https://github.com/ZainRaza14/deepRL

Continuous control with deep reinforcement learning

https://github.com/Zartris/TD3_continuous_control

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/Zartris/TD3_multi_agent_tennis

Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

https://github.com/Zhiwei-Z/PrompLimitTest

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

https://github.com/Zhiwei-Z/SeqPromp

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

https://github.com/Zhiwei-Z/prompzzw

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

https://github.com/ZhuFengdaaa/minos

MINOS: Multimodal Indoor Simulator for Navigation in Complex Environments

https://github.com/ZiyangY/IndProject-RL-in-Supply-chain

Continuous control with deep reinforcement learning

https://github.com/ZiyiZhang27/tdpo

The Dormant Neuron Phenomenon in Deep Reinforcement Learning

https://github.com/Zorrorulz/MultiAgentDDPG-Tennis

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

https://github.com/a2198699s/AI-Line-Follower

Closed-loop deep learning: generating forward models with back-propagation

https://github.com/aabbeell/reinforcementLearning.a2c.gym

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/aadeshnpn/Temporal-Credit-Assignment

Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning

https://github.com/aaron-nguyen/DDPG-UAV-Efficiency

SREC: Proactive Self-Remedy of Energy-Constrained UAV-Based Networks via Deep Reinforcement Learning

https://github.com/abbadka/quadcopter

Continuous control with deep reinforcement learning

https://github.com/abefetterman/hamstir-gym

CAD2RL: Real Single-Image Flight without a Single Real Image

https://github.com/abnerlijin/Strategy

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/abryeemessi/Wednesday

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/ac-93/soft-actor-critic

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

https://github.com/ac-93/tactile_gym_servo_control

Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation

https://github.com/acht7111020/DRL-playing-2.5D-fighting-game

Deep Reinforcement Learning for Playing 2.5D Fighting Games

https://github.com/acutronicrobotics/ros2learn

ROS2Learn: a reinforcement learning framework for ROS 2

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