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D4RL
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/qinwenluo/ssar
공식 코드Learning to Trust Bellman Updates: Selective State-Adaptive Regularization for Offline RL
https://github.com/rail-berkeley/d4rl
공식 코드https://github.com/rail-berkeley/offline_rl
공식 코드https://github.com/rail-berkeley/rlkit
공식 코드https://github.com/renming-huang/trajectorydiffuser
공식 코드Diffusion Models as Optimizers for Efficient Planning in Offline RL
https://github.com/runamu/compositional-conservatism
공식 코드Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
https://github.com/ruoqizzz/entropy-offlineRL
공식 코드Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning
https://github.com/ryanxhr/ivr
공식 코드Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
https://github.com/ryanxhr/por
공식 코드A Policy-Guided Imitation Approach for Offline Reinforcement Learning
https://github.com/sail-sg/edp
공식 코드Efficient Diffusion Policies for Offline Reinforcement Learning
https://github.com/sail-sg/misa
공식 코드Mutual Information Regularized Offline Reinforcement Learning
https://github.com/sail-sg/offbench
공식 코드Improving and Benchmarking Offline Reinforcement Learning Algorithms
https://github.com/seohongpark/fql
공식 코드https://github.com/sharkwyf/cgdt
공식 코드Critic-Guided Decision Transformer for Offline Reinforcement Learning
https://github.com/silihuang-ai/idt
공식 코드In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
https://github.com/takuseno/d3rlpy
공식 코드https://github.com/thu-ml/cep-energy-guided-diffusion
공식 코드https://github.com/thu-ml/efficient-diffusion-alignment
공식 코드Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
https://github.com/thu-ml/srpo
공식 코드Score Regularized Policy Optimization through Diffusion Behavior
https://github.com/thuml/Flowformer
공식 코드Flowformer: Linearizing Transformers with Conservation Flows
https://github.com/tianyucodings/diffusion_trusted_q_learning
공식 코드Diffusion Policies creating a Trust Region for Offline Reinforcement Learning
https://github.com/tinkoff-ai/CORL
공식 코드CORL: Research-oriented Deep Offline Reinforcement Learning Library
https://github.com/tinkoff-ai/sac-rnd
공식 코드https://github.com/tsutikgiau/valuememorygraph
공식 코드Value Memory Graph: A Graph-Structured World Model for Offline Reinforcement Learning
https://github.com/victor-wang-902/synthetic-pretrain-rl
공식 코드Pre-training with Synthetic Data Helps Offline Reinforcement Learning
https://github.com/wkh923/m3pc
공식 코드M$^3$PC: Test-time Model Predictive Control for Pretrained Masked Trajectory Model
https://github.com/yingyichen-cyy/PrimalAttention
공식 코드Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
https://github.com/yk7333/drnd
공식 코드Exploration and Anti-Exploration with Distributional Random Network Distillation
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/zhaoyi11/adaptive_bc
공식 코드Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning
https://github.com/zhendong-wang/diffusion-policies-for-offline-rl
공식 코드Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
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
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.