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/anyasims/edge-of-reach

공식 코드

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

https://github.com/anyasims/edge-of-reach-ravl

공식 코드

The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

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

공식 코드

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

https://github.com/apexrl/coil

공식 코드

Curriculum Offline Imitation Learning

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

공식 코드

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

https://github.com/arjunbhorkar/ReViND

공식 코드

Offline Reinforcement Learning for Visual Navigation

https://github.com/artberryx/pma

공식 코드

Predictable MDP Abstraction for Unsupervised Model-Based RL

https://github.com/asap7772/ptr

공식 코드

Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials

https://github.com/asappresearch/dialogue-offline-rl

공식 코드

On the Effectiveness of Offline RL for Dialogue Response Generation

https://github.com/aslanides/aixijs

공식 코드

Generalised Discount Functions applied to a Monte-Carlo AImu Implementation

https://github.com/atavakol/action-branching-agents

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Action Branching Architectures for Deep Reinforcement Learning

https://github.com/atavakol/action-hypergraph-networks

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Learning to Represent Action Values as a Hypergraph on the Action Vertices

https://github.com/automl/HPO_for_RL

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On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

https://github.com/autonomousagentslab/curiousreplay

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Curious Replay for Model-based Adaptation

https://github.com/aviralkumar2907/CQL

공식 코드

Conservative Q-Learning for Offline Reinforcement Learning

https://github.com/baggepinnen/LPVSpectral.jl

공식 코드

Machine Learning and System Identification for Estimation in Physical Systems

https://github.com/baggepinnen/LTVModels.jl

공식 코드

Machine Learning and System Identification for Estimation in Physical Systems

https://github.com/baggepinnen/Robotlib.jl

공식 코드

Machine Learning and System Identification for Estimation in Physical Systems

https://github.com/baichenjia/pbrl

공식 코드

Pessimistic Bootstrapping for Uncertainty-Driven Offline Reinforcement Learning

https://github.com/baichenjia/utds

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Pessimistic Value Iteration for Multi-Task Data Sharing in Offline Reinforcement Learning

https://github.com/baimingc/dambrl

공식 코드

Delay-Aware Model-Based Reinforcement Learning for Continuous Control

https://github.com/baitingluo/l-map

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Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction

https://github.com/batra-mlp-lab/va_mbrl

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Model-Advantage and Value-Aware Models for Model-Based Reinforcement Learning: Bridging the Gap in Theory and Practice

https://github.com/battlewen/ro2o

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Towards Robust Offline-to-Online Reinforcement Learning via Uncertainty and Smoothness

https://github.com/bcornelusse/microgridRLsimulator

공식 코드

Lifelong Control of Off-grid Microgrid with Model Based Reinforcement Learning

https://github.com/befelix/safe_learning

공식 코드

Safe Model-based Reinforcement Learning with Stability Guarantees

https://github.com/ben-eysenbach/ac-connection

공식 코드

A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning

https://github.com/ben-eysenbach/mnm

공식 코드

Mismatched No More: Joint Model-Policy Optimization for Model-Based RL

https://github.com/betray12138/UNICORN

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Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning

https://github.com/biorobotics/learning_modular_policies

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Learning Modular Robot Control Policies

https://github.com/bit1029public/hrssm

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Learning Latent Dynamic Robust Representations for World Models

https://github.com/bit1029public/offline_bpr

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Behavior Prior Representation learning for Offline Reinforcement Learning

https://github.com/bkkgbkjb/oppo

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Beyond Reward: Offline Preference-guided Policy Optimization

https://github.com/blakeyy/neuromorphic_dreaming

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Neuromorphic dreaming: A pathway to efficient learning in artificial agents

https://github.com/borealisai/sasrec-ccql

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Robust Reinforcement Learning Objectives for Sequential Recommender Systems

https://github.com/boschresearch/dist-mbrl

공식 코드

Value-Distributional Model-Based Reinforcement Learning

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