Papers with Code 아카이브
Offline RL
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/xiaoyinliu0714/micro
공식 코드MICRO: Model-Based Offline Reinforcement Learning with a Conservative Bellman Operator
https://github.com/xingshuaihuang/dtlight
공식 코드Traffic Signal Control Using Lightweight Transformers: An Offline-to-Online RL Approach
https://github.com/xuefeng-cs/a3rl
공식 코드Active Advantage-Aligned Online Reinforcement Learning with Offline Data
https://github.com/yangrui2015/awgcsl
공식 코드Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL
https://github.com/yangrui2015/goat
공식 코드What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?
https://github.com/yangrui2015/riql
공식 코드Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
https://github.com/yangrui2015/rorl
공식 코드RORL: Robust Offline Reinforcement Learning via Conservative Smoothing
https://github.com/yangrui2015/uwmsg
공식 코드Corruption-Robust Offline Reinforcement Learning with General Function Approximation
https://github.com/yaotang23/currmask
공식 코드https://github.com/yassinech/caps
공식 코드Constraint-Adaptive Policy Switching for Offline Safe Reinforcement Learning
https://github.com/yifeizhou02/hnpg
공식 코드Offline Data Enhanced On-Policy Policy Gradient with Provable Guarantees
https://github.com/yingyichen-cyy/PrimalAttention
공식 코드Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
https://github.com/yiqinyang/icq
공식 코드Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
https://github.com/yqpqry/sqog
공식 코드Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
https://github.com/yuanying-cc/td3-rkl
공식 코드TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
https://github.com/yueyang130/odpr
공식 코드https://github.com/yueyang130/seem
공식 코드Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
https://github.com/zaiyan-x/drqi
공식 코드https://github.com/zbzhu99/madiff
공식 코드https://github.com/zeyubian/2feope
공식 코드https://github.com/zeyuzhang1901/unified-off-policy-ltr-neurips2023
공식 코드Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
https://github.com/zhanzxy5/MOPP
공식 코드https://github.com/zhaoyi11/adaptive_bc
공식 코드Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
https://github.com/zhaoyizhou1123/mbrcsl
공식 코드https://github.com/zhendong-wang/diffusion-policies-for-offline-rl
공식 코드Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
https://github.com/zheng0428/more_
공식 코드MORE-3S:Multimodal-based Offline Reinforcement Learning with Shared Semantic Spaces
https://github.com/zhengyinan-air/fisor
공식 코드Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
https://github.com/zhouzypaul/wsrl
공식 코드Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data
https://gitlab.com/hdonancio/pumpscheduling
공식 코드The Pump Scheduling Problem: A Real-World Scenario for Reinforcement Learning
https://agit.ai/Polixir/OfflineRL
https://github.com/2023-MindSpore-1/ms-code-220/tree/main/pmdb
Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/decision_transformer
Decision Transformer: Reinforcement Learning via Sequence Modeling
https://github.com/Amadeus979/decision-transformer
Decision Transformer: Reinforcement Learning via Sequence Modeling
https://github.com/Asap7772/OfflineRlWorkflow
A Workflow for Offline Model-Free Robotic Reinforcement Learning
https://github.com/BY571/CQL
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.