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Deep Reinforcement Learning

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코드

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

https://bitbucket.org/catk1ns0n/repr_public

공식 코드

Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting

https://bitbucket.org/scee_ietr/malin-multi-armed-bandit-learning-for-iot-networks-with-grc

공식 코드

Reinforcement Learning for Physical Layer Communications

https://github.com/1jsingh/semantic-guidance

공식 코드

Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings

https://github.com/32af3611/ai4mat-neurips-workshop-2022

공식 코드

Actively Learning Costly Reward Functions for Reinforcement Learning

https://github.com/42jaylonw/rrc2021threewolves

공식 코드

Real-World Dexterous Object Manipulation based Deep Reinforcement Learning

https://github.com/846468230/RoSGAS

공식 코드

RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture Search

https://github.com/A2R-Lab/Just-Round

공식 코드

Just Round: Quantized Observation Spaces Enable Memory Efficient Learning of Dynamic Locomotion

https://github.com/AI4Finance-Foundation/FinRL

공식 코드

FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance

https://github.com/AMR-/JackalCrowdEnv

공식 코드

XAI-N: Sensor-based Robot Navigation using Expert Policies and Decision Trees

https://github.com/ASU-APG/Targeted-Physical-Adversarial-Attacks-on-AD

공식 코드

Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns

https://github.com/Abdulmajid-Murad/IoT-Sensor-Gym

공식 코드

Autonomous Management of Energy-Harvesting IoT Nodes Using Deep Reinforcement Learning

https://github.com/Abdulmajid-Murad/adaptive-sensing

공식 코드

Information-Driven Adaptive Sensing Based on Deep Reinforcement Learning

https://github.com/AdamStelmaszczyk/learning2run

공식 코드

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

https://github.com/AdrienLin1/MACDPP

공식 코드

Effective Multi-Agent Deep Reinforcement Learning Control with Relative Entropy Regularization

https://github.com/AlbertoSinigaglia/double_pendulum

공식 코드

AI Olympics challenge with Evolutionary Soft Actor Critic

https://github.com/Alessiobrini/Deep-Reinforcement-Trading-with-Predictable-Returns

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Deep Reinforcement Trading with Predictable Returns

https://github.com/AlexandreChenu/DCIL_XPAG

공식 코드

Leveraging Sequentiality in Reinforcement Learning from a Single Demonstration

https://github.com/AlexandreChenu/dcil

공식 코드

Divide & Conquer Imitation Learning

https://github.com/Algolzw/SPAC-Deformable-Registration

공식 코드

Stochastic Actor-Executor-Critic for Image-to-Image Translation

https://github.com/AmmarFayad/Behavioral-Actor-Critic

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Behavior-Guided Actor-Critic: Improving Exploration via Learning Policy Behavior Representation for Deep Reinforcement Learning

https://github.com/ArantxaCasanova/ralis

공식 코드

Reinforced active learning for image segmentation

https://github.com/Ardavans/DSR

공식 코드

Deep Successor Reinforcement Learning

https://github.com/BIT-MCS/Cadre

공식 코드

CADRE: A Cascade Deep Reinforcement Learning Framework for Vision-based Autonomous Urban Driving

https://github.com/BME-SmartLab/rl-wds

공식 코드

Deep Reinforcement Learning for Real-Time Optimization of Pumps in Water Distribution Systems

https://github.com/BNN-UPC/ENERO

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ENERO: Efficient Real-Time WAN Routing Optimization with Deep Reinforcement Learning

https://github.com/BU-DEPEND-Lab/DRIBO

공식 코드

DRIBO: Robust Deep Reinforcement Learning via Multi-View Information Bottleneck

https://github.com/Baichenjia/OB2I

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Principled Exploration via Optimistic Bootstrapping and Backward Induction

https://github.com/BarakGahtan/5GRIE

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5G Routing Interfered Environment

https://github.com/Bilibili/LastOrder

공식 코드

Macro action selection with deep reinforcement learning in StarCraft

https://github.com/BlueFisher/RL-PPO-with-Unity

공식 코드

Proximal Policy Optimization with Mixed Distributed Training

https://github.com/BorealisAI/pommerman-baseline

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Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition

https://github.com/Breakend/ReproducibilityInContinuousPolicyGradientMethods

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Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

https://github.com/BruntonUWBio/plumetracknets

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Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes

https://github.com/CAiM-lab/PPO

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Reinforcement Learning of Musculoskeletal Control from Functional Simulations

https://github.com/CFMTech/Deep-RL-for-Portfolio-Optimization

공식 코드

Deep Deterministic Portfolio Optimization

https://github.com/CLAIR-LAB-TECHNION/multi_taxi

공식 코드

Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning

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