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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/VasaKiDD/alpha-regex

Ranked Reward: Enabling Self-Play Reinforcement Learning for Combinatorial Optimization

https://github.com/VasaKiDD/end-to-end-drug-discovery

Fractal AI: A fragile theory of intelligence

https://github.com/Vatsala17/Vatsala17

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

https://github.com/Veloc1tyE/Drift

World Models

https://github.com/VictorZuanazzi/Project_RL

Prioritized Experience Replay

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/Wadaboa/flatland-challenge

Revisiting the Softmax Bellman Operator: New Benefits and New Perspective

https://github.com/Wanqianxn/usfa

Universal Successor Features Approximators

https://github.com/WarClans612/deep_learning_final

Searching for Activation Functions

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/WessZumino/expectation_propagation

Searching for Activation Functions

https://github.com/WessZumino/meanfield-theory-of-activation-functions

Searching for Activation Functions

https://github.com/Westlake-AI/openmixup

Searching for Activation Functions

https://github.com/WilsonWangTHU/mbbl-metrpo

Model-Ensemble Trust-Region Policy Optimization

https://github.com/Windxy/BayesianCNN-Based-on-Paddle

Weight Uncertainty in Neural Networks

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

Continuous control with deep reinforcement learning

https://github.com/WolfNiu/polite-dialogue-generation

Polite Dialogue Generation Without Parallel Data

https://github.com/Wordbe/GradCAM3D

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

https://github.com/WuJie1010/Temporally-language-grounding

Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos

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/Xaniar87/SAN_SQuAD2

Stochastic Answer Networks for Machine Reading Comprehension

https://github.com/XiWen0627/MaxEnIRLinCycling

Maximum Entropy Deep Inverse Reinforcement Learning

https://github.com/XiangboGaoBarry/TexasHoldemAI

RLCard: A Toolkit for Reinforcement Learning in Card Games

https://github.com/XinbangZhang/DSO-NAS

You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization

https://github.com/XingxingZhang/dress

Sentence Simplification with Deep Reinforcement Learning

https://github.com/Xingyu-Lin/mbpo_pytorch

When to Trust Your Model: Model-Based Policy Optimization

https://github.com/Xking8/Nav_ml-agent-v5

Unity: A General Platform for Intelligent Agents

https://github.com/XuehaiPan/Soft-Actor-Critic

Soft Actor-Critic Algorithms and Applications

https://github.com/XueyingBai/Model-Based-Reinforcement-Learning-for-Online-Recommendation

Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation

https://github.com/YHL04/agent57

Never Give Up: Learning Directed Exploration Strategies

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

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

https://github.com/YaCpotato/B4ResearchDeepaugment

Neural Architecture Search with Reinforcement Learning

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