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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/SmartSystems-UniAndes/ML_for_Solar_PV_Systems

A Centralised Soft Actor Critic Deep Reinforcement Learning Approach to District Demand Side Management through CityLearn

https://github.com/Sohojoe/ActiveRagdollStyleTransfer

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

https://github.com/Souphis/mobile_robot_rl

Continuous control with deep reinforcement learning

https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

https://github.com/StanfordVL/ac-teach

AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers

https://github.com/Steinheilig/Imbiss

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

https://github.com/Steven-Ho/multiagent-particle-envs

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

https://github.com/Stippler/cow-simulator

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

https://github.com/SudeepDasari/visual_foresight

Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control

https://github.com/SwarajPawar/Discrete-BCQ

Benchmarking Batch Deep Reinforcement Learning Algorithms

https://github.com/T3chy/DDPG

Continuous control with deep reinforcement learning

https://github.com/TakaOsa/LTD3

Discovering Diverse Solutions in Deep Reinforcement Learning by Maximizing State-Action-Based Mutual Information

https://github.com/TaoQin/taoqin.github.io

Suphx: Mastering Mahjong with Deep Reinforcement Learning

https://github.com/TeaganLi/ICRA2020_manipulation

Learning Hierarchical Control for Robust In-Hand Manipulation

https://github.com/Teslatic/SC2-Freiburg

StarCraft II: A New Challenge for Reinforcement Learning

https://github.com/TheFebrin/DeepRL-Pong

Playing Atari with Deep Reinforcement Learning

https://github.com/TheInfamousWayne/ddpg

Continuous control with deep reinforcement learning

https://github.com/TinkeringCode/Neural-Fictitous-Self-Play

Deep Reinforcement Learning from Self-Play in Imperfect-Information Games

https://github.com/TobiKick/DL_LF2

Deep Reinforcement Learning for Playing 2.5D Fighting Games

https://github.com/TonghanWang/DOP

Multiagent Cooperation and Competition with Deep Reinforcement Learning

https://github.com/TonghanWang/NDQ

Multiagent Cooperation and Competition with Deep Reinforcement Learning

https://github.com/TristanBertin/Reinforcement_Learning

Modern Deep Reinforcement Learning Algorithms

https://github.com/UlisseMini/procgen-tools

Goal Misgeneralization in Deep Reinforcement Learning

https://github.com/UnibucProjects/DeepRLRecommenderSystem

Deep Reinforcement Learning for List-wise Recommendations

https://github.com/UrosOgrizovic/SimpleGoogleQuickdraw

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

https://github.com/V0LsTeR/DQN_heap

Dopamine: A Research Framework for Deep Reinforcement Learning

https://github.com/V0LsTeR/dopamine_prioritized_buffer

Dopamine: A Research Framework for Deep Reinforcement Learning

https://github.com/VasaKiDD/TD3-deep-rl-research

Continuous control with deep reinforcement learning

https://github.com/Vatsala17/Vatsala17

Decentralized Computation Offloading for Multi-User Mobile Edge Computing: A Deep Reinforcement Learning Approach

https://github.com/VictorZuanazzi/Project_RL

The Effects of Memory Replay in Reinforcement Learning

https://github.com/VincentYu68/SymmetryCurriculumLocomotion

Learning Symmetric and Low-energy Locomotion

https://github.com/WVik/DeepRL-for-Graphs

Graph-based State Representation for Deep Reinforcement Learning

https://github.com/Wadaboa/cpr-appropriation

A multi-agent reinforcement learning model of common-pool resource appropriation

https://github.com/WeiChengTseng/Pytorch-PCGrad

Gradient Surgery for Multi-Task Learning

https://github.com/Wentworth1996/Summer_Intern_Progress

Playing Atari with Deep Reinforcement Learning

https://github.com/WittmannF/quadcopter-best-practices

Continuous control with deep reinforcement learning

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.