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Offline RL

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

https://github.com/2019chengong/offline_rl_poisoner

공식 코드

BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets

https://github.com/2019chengong/trajdeleter

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TrajDeleter: Enabling Trajectory Forgetting in Offline Reinforcement Learning Agents

https://github.com/Altriaex/multi_source_behavior_modeling

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Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning

https://github.com/AndssY/DeMa

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Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?

https://github.com/ArronDZhang/ROLeR

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ROLeR: Effective Reward Shaping in Offline Reinforcement Learning for Recommender Systems

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/Facebear-ljx/DOGE

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When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning

https://github.com/Holmeswww/ml-uwac

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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/HxLyn3/ADMPO

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Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning

https://github.com/Improbable-AI/dw-offline-rl

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Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets

https://github.com/JannerM/trajectory-transformer

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Offline Reinforcement Learning as One Big Sequence Modeling Problem

https://github.com/JasonMa2016/CODAC

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Conservative Offline Distributional Reinforcement Learning

https://github.com/LiangZhang1996/DataLight

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DataLight: Offline Data-Driven Traffic Signal Control

https://github.com/MAOYIXIU/SCAS

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Offline Reinforcement Learning with OOD State Correction and OOD Action Suppression

https://github.com/MIRALab-USTC/RL-TRACER

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Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions

https://github.com/MLD3/OfflineRL_ModelSelection

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Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings

https://github.com/MaxSobolMark/OOO

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Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias

https://github.com/MiaHRT/CAWR

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CAWR: Corruption-Averse Advantage-Weighted Regression for Robust Policy Optimization

https://github.com/OpenNLPLab/cosFormer

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cosFormer: Rethinking Softmax in Attention

https://github.com/PrajwalKoirala/LSPC-Safe-Offline-RL

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Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning

https://github.com/PrajwalKoirala/Offline-Reinforcement-Learning-with-Decision-Tree-Regression

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Solving Offline Reinforcement Learning with Decision Tree Regression

https://github.com/QinwenLuo/OCR-CFT

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Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL

https://github.com/SaminYeasar/sparse_reg

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Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity

https://github.com/THUDM/LongReward

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LongReward: Improving Long-context Large Language Models with AI Feedback

https://github.com/TU2021/DTR

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In-Dataset Trajectory Return Regularization for Offline Preference-based Reinforcement Learning

https://github.com/ZhengyaoJiang/latentplan

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Efficient Planning in a Compact Latent Action Space

https://github.com/abaheti95/lol-rl

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Leftover Lunch: Advantage-based Offline Reinforcement Learning for Language Models

https://github.com/adanielnoel/Active-Inference-Capsule

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Online reinforcement learning with sparse rewards through an active inference capsule

https://github.com/ahundt/costar_dataset

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The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/ahundt/enas

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The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/ai-secure/copa

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COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks

https://github.com/anqili/mahalo

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MAHALO: Unifying Offline Reinforcement Learning and Imitation Learning from Observations

https://github.com/aopolin-lv/DecisionMamba

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Decision Mamba: A Multi-Grained State Space Model with Self-Evolution Regularization for Offline RL

https://github.com/apexrl/coil

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Curriculum Offline Imitation Learning

https://github.com/apple/ml-uwac

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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/arjunbhorkar/ReViND

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Offline Reinforcement Learning for Visual Navigation

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