Papers with Code 아카이브

Reinforcement Learning

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코드

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

https://github.com/JiqianDong/GCQ_source

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

https://github.com/Jmak12/Iris1

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

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/tf2multiagentrl

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

https://github.com/John-Yu/leelaApplication

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

https://github.com/JohnKurian/R2D2

Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning

https://github.com/JohnYKiyo/coco_trial

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

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/JonasRSV/PPO

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/JonathanVanDyke/ML-Unity

Unity: A General Platform for Intelligent Agents

https://github.com/JoostHuizinga/cmoea

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm

https://github.com/JoostHuizinga/cmoea_experiments

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm

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

Continuous control with deep reinforcement learning

https://github.com/JoseVillagranE/Pointer-Networks

Neural Combinatorial Optimization with Reinforcement Learning

https://github.com/JosephElHachem/GradCam

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

https://github.com/JuHyun-E/Attention-ResNet50

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

https://github.com/JuHyun-E/Attention_in_NN

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

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/JuliaPOMDP/FactoredValueMCTS.jl

Scalable Planning and Learning for Multiagent POMDPs: Extended Version

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

Deep reinforcement learning from human preferences

https://github.com/JuneFeng/RelationClassification-RL

Reinforcement Learning for Relation Classification from Noisy Data

https://github.com/JunkyByte/HER_DQN

Hindsight Experience Replay

https://github.com/JunnYu/x-transformers-paddle

Stabilizing Transformers for Reinforcement Learning

https://github.com/JunrQ/NAS

DARTS: Differentiable Architecture Search

https://github.com/Jupaoqq/Jupaoqq_LaRL

Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models

https://github.com/JustinStitt/acrobotDDQN

Deep Reinforcement Learning with Double Q-learning

https://github.com/Justkim/random-network-distillation-pytorch

Exploration by Random Network Distillation

https://github.com/Jzar/Space-Invaders-DQN

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/K-tang-mkv/baseRLAlgorithm

Playing Atari with Deep Reinforcement Learning

https://github.com/KAIST-AILab/deeprl_practice_colab

Continuous control with deep reinforcement learning

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