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Reinforcement Learning

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코드

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

https://github.com/DanielTakeshi/DCUR

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/DanielTakeshi/dqn

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

https://github.com/DanyWind/fastai_bs_finder

An Empirical Model of Large-Batch Training

https://github.com/DartEnv/dart-env

OpenAI Gym

https://github.com/DartML/PPO-Stein-Control-Variate

Action-depedent Control Variates for Policy Optimization via Stein's Identity

https://github.com/Dascka/dl_q-learning_comparator

Deep Reinforcement Learning that Matters

https://github.com/DataCanvasIO/Hypernets

Neural Architecture Search with Reinforcement Learning

https://github.com/DataScienceNigeria/D-Kitty-D-Claw.-Robotics-Benchmarks-for-Learning-with-Low-Cost-Robots-

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

https://github.com/DataXujing/PNASNet_pytorch

Progressive Neural Architecture Search

https://github.com/DavidCastilloAlvarado/Path-planning-and-Reinforcement-Learning

Proximal Policy Optimization Algorithms

https://github.com/DavidJanz/successor_uncertainties_atari

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

https://github.com/DavidJanz/successor_uncertainties_tabular

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

https://github.com/DavidLee-4032/Graph_Opt

Learning Combinatorial Optimization Algorithms over Graphs

https://github.com/DdATM/ML-FlappyBird

Unity: A General Platform for Intelligent Agents

https://github.com/Deci-AI/super-gradients

Progressive Neural Architecture Search

https://github.com/DeepGraphLearning/RecommenderSystems

Ekar: An Explainable Method for Knowledge Aware Recommendation

https://github.com/DeepLearningCUCS/RLVRP

Reinforcement Learning for Solving the Vehicle Routing Problem

https://github.com/Deepak3994/Grad-Cam

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/Deepak3994/grad-cam-editted

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/Deepest-Project/WorldModels-A3C

World Models

https://github.com/Dekki-Aero/DDPG

Continuous control with deep reinforcement learning

https://github.com/Delavari-Alireza/Decision_Transformer_Sequence-Modeling_Deep_Reinforcement_Learning

Decision Transformer: Reinforcement Learning via Sequence Modeling

https://github.com/Denbergvanthijs/imbDRL

Deep Reinforcement Learning with Double Q-learning

https://github.com/DerrickGXD/unsupervised-keypoints

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/DevSlem/AINE-DRL

Proximal Policy Optimization Algorithms

https://github.com/DevSlem/OfflineRL/blob/main/chap1_introduction.ipynb

Off-Policy Actor-Critic

https://github.com/DianYu420376/multi-agent-RL-numerical-simulation

Distributed Reinforcement Learning for Decentralized Linear Quadratic Control: A Derivative-Free Policy Optimization Approach

https://github.com/Div99/IQ-Learn

Generative Adversarial Imitation Learning

https://github.com/Dlut-lab-zmn/Image-Captioning-Attack

Self-critical Sequence Training for Image Captioning

https://github.com/DoctorLiQ/AutoML

DARTS: Differentiable Architecture Search

https://github.com/Dorozhko-Anton/go-explore

Go-Explore: a New Approach for Hard-Exploration Problems

https://github.com/DrArryYao/RL-SC

Flow: A Modular Learning Framework for Mixed Autonomy Traffic

https://github.com/DrJupiter/Deep-Reinforcement-Rubiks-Cube-Solver

Revisiting Fundamentals of Experience Replay

https://github.com/Duan-JM/awesome-papers-fewshot

Meta-Learning in Neural Networks: A Survey

https://github.com/DuaneNielsen/keypoints

Unsupervised Learning of Object Keypoints for Perception and Control

https://github.com/DuaneNielsen/rnd

Exploration by Random Network Distillation

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