Papers with Code 아카이브

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/qiwang067/CoWorld

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Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning

https://github.com/quantumiracle/consistency_model_for_reinforcement_learning

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Consistency Models as a Rich and Efficient Policy Class for Reinforcement Learning

https://github.com/rail-berkeley/d4rl

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D4RL: Datasets for Deep Data-Driven Reinforcement Learning

https://github.com/rail-berkeley/offline_rl

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D4RL: Datasets for Deep Data-Driven Reinforcement Learning

https://github.com/rail-berkeley/rlkit

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Offline Reinforcement Learning with Implicit Q-Learning

https://github.com/ramp-kits/rl_simulator

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Model-based micro-data reinforcement learning: what are the crucial model properties and which model to choose?

https://github.com/ran-weii/objective_mismatch_papers

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A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning

https://github.com/realwenlongwang/drama

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Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient

https://github.com/reinholdm/offline-pre-trained-multi-agent-decision-transformer

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Offline Pre-trained Multi-Agent Decision Transformer: One Big Sequence Model Tackles All SMAC Tasks

https://github.com/remosasso/psdrl

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Posterior Sampling for Deep Reinforcement Learning

https://github.com/renming-huang/trajectorydiffuser

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Diffusion Models as Optimizers for Efficient Planning in Offline RL

https://github.com/resibots/kaushik_2020_famle

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Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors

https://github.com/rlatjddbs/ssd

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Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL

https://github.com/rmbpo-eval/rmbpo-eval

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Robust Model-Based Reinforcement Learning with an Adversarial Auxiliary Model

https://github.com/romina72/paml

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Policy-Aware Model Learning for Policy Gradient Methods

https://github.com/roosephu/slbo

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Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees

https://github.com/roythuly/obac

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Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL

https://github.com/runamu/compositional-conservatism

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Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning

https://github.com/ruoqizzz/entropy-offlineRL

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Entropy-regularized Diffusion Policy with Q-Ensembles for Offline Reinforcement Learning

https://github.com/ryanshea10/personachat_offline_rl

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Building Persona Consistent Dialogue Agents with Offline Reinforcement Learning

https://github.com/ryanxhr/dwbc

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Discriminator-Weighted Offline Imitation Learning from Suboptimal Demonstrations

https://github.com/ryanxhr/ivr

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Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization

https://github.com/ryanxhr/por

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A Policy-Guided Imitation Approach for Offline Reinforcement Learning

https://github.com/ryeii/CLUE

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A Safe and Data-efficient Model-based Reinforcement Learning System for HVAC Control

https://github.com/ryeii/veri_hvac

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Go Beyond Black-box Policies: Rethinking the Design of Learning Agent for Interpretable and Verifiable HVAC Control

https://github.com/sail-sg/edp

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Efficient Diffusion Policies for Offline Reinforcement Learning

https://github.com/sail-sg/misa

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Mutual Information Regularized Offline Reinforcement Learning

https://github.com/sail-sg/offbench

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Improving and Benchmarking Offline Reinforcement Learning Algorithms

https://github.com/sail-sg/oper

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Decoupled Prioritized Resampling for Offline RL

https://github.com/sail-sg/rosmo

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Efficient Offline Policy Optimization with a Learned Model

https://github.com/samholt/neurallaplacecontrol

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Neural Laplace Control for Continuous-time Delayed Systems

https://github.com/sarodyatawatta/hintrl

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Hint assisted reinforcement learning: an application in radio astronomy

https://github.com/scottemmons/rvs

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RvS: What is Essential for Offline RL via Supervised Learning?

https://github.com/seanjparker/rlflow

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RLFlow: Optimising Neural Network Subgraph Transformation with World Models

https://github.com/seanrsinclair/AdaptiveQLearning

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Adaptive Discretization for Model-Based Reinforcement Learning

https://github.com/sebascuri/hucrl

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Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning

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