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General Reinforcement Learning

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하위 태스크: 2
평가표: 6
보존된 평가 기록: 12

코드

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

https://github.com/hardikparwana/foresee

공식 코드

FORESEE: Prediction with Expansion-Compression Unscented Transform for Online Policy Optimization

https://github.com/hari-sikchi/DVL

공식 코드

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning

https://github.com/harrieo/2022-doubly-robust-ltr

공식 코드

Doubly-Robust Estimation for Correcting Position-Bias in Click Feedback for Unbiased Learning to Rank

https://github.com/harryzhangOG/salved

공식 코드

Safe Deep Model-Based Reinforcement Learning with Lyapunov Functions

https://github.com/hemerson1/offline-glucose

공식 코드

Offline Reinforcement Learning for Safer Blood Glucose Control in People with Type 1 Diabetes

https://github.com/hmomin/networkgym

공식 코드

NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation

https://github.com/holarissun/rewardshifting

공식 코드

Optimistic Curiosity Exploration and Conservative Exploitation with Linear Reward Shaping

https://github.com/homangab/gradcem

공식 코드

Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization

https://github.com/hori-group/two-step-design

공식 코드

Two-step reinforcement learning for model-free redesign of nonlinear optimal regulator

https://github.com/huawei-noah/HEBO/tree/master/PMDB

공식 코드

Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief

https://github.com/huawei-noah/hebo

공식 코드

Model-Based Offline Reinforcement Learning with Pessimism-Modulated Dynamics Belief

https://github.com/huihuichyan/think-j

공식 코드

Think-J: Learning to Think for Generative LLM-as-a-Judge

https://github.com/hukz18/defog

공식 코드

Decision Transformer under Random Frame Dropping

https://github.com/hwang-ua/inac_pytorch

공식 코드

The In-Sample Softmax for Offline Reinforcement Learning

https://github.com/idiap/fast-transformers

공식 코드

Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

https://github.com/ikostrikov/implicit_q_learning

공식 코드

Offline Reinforcement Learning with Implicit Q-Learning

https://github.com/imoneoi/RSP_JAX

공식 코드

Are Expressive Models Truly Necessary for Offline RL?

https://github.com/improbable-ai/harness-offline-rl

공식 코드

Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting

https://github.com/innixma/dex

공식 코드

Dex: Incremental Learning for Complex Environments in Deep Reinforcement Learning

https://github.com/ivy-dl/memory

공식 코드

End-to-End Egospheric Spatial Memory

https://github.com/jaewoopudding/gta

공식 코드

GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning

https://github.com/janisgeise/mb_drl_for_accelerated_learning_from_cfd

공식 코드

Model-based deep reinforcement learning for accelerated learning from flow simulations

https://github.com/jannerm/diffuser

공식 코드

Planning with Diffusion for Flexible Behavior Synthesis

https://github.com/jasonma2016/gofar

공식 코드

Swapped goal-conditioned offline reinforcement learning

https://github.com/jbr-ai-labs/mamba

공식 코드

Scalable Multi-Agent Model-Based Reinforcement Learning

https://github.com/jc043/cpl

공식 코드

Predictive Experience Replay for Continual Visual Control and Forecasting

https://github.com/jcoreyes/OP3

공식 코드

Entity Abstraction in Visual Model-Based Reinforcement Learning

https://github.com/jerry99s/NonZeroSum_Driving

공식 코드

Non-zero-sum Game Control for Multi-vehicle Driving via Reinforcement Learning

https://github.com/jessefarebro/distributional-sr

공식 코드

A Distributional Analogue to the Successor Representation

https://github.com/jhu-lcsr/costar_plan

공식 코드

The CoSTAR Block Stacking Dataset: Learning with Workspace Constraints

https://github.com/jity16/when-to-update-your-model-constrained-model-based-reinforcement-learning

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When to Update Your Model: Constrained Model-based Reinforcement Learning

https://github.com/jnousi/po4ao

공식 코드

Laboratory Experiments of Model-based Reinforcement Learning for Adaptive Optics Control

https://github.com/johannesack/offlinerlstructurednonstationarity

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Offline Reinforcement Learning from Datasets with Structured Non-Stationarity

https://github.com/jrobine/twm

공식 코드

Transformer-based World Models Are Happy With 100k Interactions

https://github.com/juancamilog/kusanagi

공식 코드

Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning

https://github.com/juancamilog/robot_learning

공식 코드

Synthesizing Neural Network Controllers with Probabilistic Model based Reinforcement Learning

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