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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/Denys88/rl_games

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DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality

https://github.com/Detry322/DeepRole

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Finding Friend and Foe in Multi-Agent Games

https://github.com/DevSlem/Mol-AIR

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Mol-AIR: Molecular Reinforcement Learning with Adaptive Intrinsic Rewards for Goal-directed Molecular Generation

https://github.com/DexterZeng/CEAFF

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Reinforcement Learning based Collective Entity Alignment with Adaptive Features

https://github.com/Dinu23/Quantum-Tiq-Taq-Toe

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Reinforcement learning for Quantum Tiq-Taq-Toe

https://github.com/DonsetPG/fenics-DRL

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A review on Deep Reinforcement Learning for Fluid Mechanics

https://github.com/DonsetPG/narya

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Evaluating Soccer Player: from Live Camera to Deep Reinforcement Learning

https://github.com/Dtrycode/ToupleGDD

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ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

https://github.com/EduardoGarrido90/micro_agents

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Deep Reinforcement Learning Agents for Strategic Production Policies in Microeconomic Market Simulations

https://github.com/EdwardJamesYoung/RL-portfolio-pursuit

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Reinforcement Learning applied to Insurance Portfolio Pursuit

https://github.com/Ekim-Yurtsever/Hybrid-DeepRL-Automated-Driving

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Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving

https://github.com/ElisevanderPol/mdp-homomorphic-networks

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MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

https://github.com/ElisevanderPol/prae

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Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

https://github.com/EmptyJackson/groove

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Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design

https://github.com/EndingCredits/Object-Based-RL

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Learning to Play General Video-Games via an Object Embedding Network

https://github.com/EndingCredits/json2vec

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A Framework for End-to-End Learning on Semantic Tree-Structured Data

https://github.com/EricSteinberger/DREAM

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DREAM: Deep Regret minimization with Advantage baselines and Model-free learning

https://github.com/Eulring/GoSum

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GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state

https://github.com/Eversee22/Policy-GNN

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Policy-GNN: Aggregation Optimization for Graph Neural Networks

https://github.com/FMZennaro/CTF-RL

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Modeling Penetration Testing with Reinforcement Learning Using Capture-the-Flag Challenges: Trade-offs between Model-free Learning and A Priori Knowledge

https://github.com/FMZennaro/CTF-SQL

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Simulating SQL Injection Vulnerability Exploitation Using Q-Learning Reinforcement Learning Agents

https://github.com/FOCAL-ICLR/FOCAL-ICLR

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FOCAL: Efficient Fully-Offline Meta-Reinforcement Learning via Distance Metric Learning and Behavior Regularization

https://github.com/FXDevailly/IG-RL

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IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control

https://github.com/Facebear-ljx/DOGE

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When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning

https://github.com/Facebear-ljx/PROTO

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PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

https://github.com/Farama-Foundation/PettingZoo

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PettingZoo: Gym for Multi-Agent Reinforcement Learning

https://github.com/FarnazAdib/Crash_course_on_RL

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A Crash Course on Reinforcement Learning

https://github.com/FaroukY/FillInMinimization

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ReFill: Reinforcement Learning for Fill-In Minimization

https://github.com/Feicheng-Wang/LQAC_code

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Exact Asymptotics for Linear Quadratic Adaptive Control

https://github.com/FlemmingKondrup/DeepVent

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Towards Safe Mechanical Ventilation Treatment Using Deep Offline Reinforcement Learning

https://github.com/FlorenceFeng/StateDecoding

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Provably Efficient Exploration for Reinforcement Learning Using Unsupervised Learning

https://github.com/FlorianRupp/g-pcgrl

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G-PCGRL: Procedural Graph Data Generation via Reinforcement Learning

https://github.com/FortsAndMills/Learning-Reinforcement-Learning

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Modern Deep Reinforcement Learning Algorithms

https://github.com/FragileTheory/FractalAI

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Fractal AI: A fragile theory of intelligence

https://github.com/Francesco-Sovrano/Partitioned-A3C-for-RogueInABox

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Crawling in Rogue's dungeons with (partitioned) A3C

https://github.com/Friedrich1006/ESNAC

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Learnable Embedding Space for Efficient Neural Architecture Compression

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