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Reinforcement Learning

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코드

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

https://github.com/CODE-SUBMIT/simulator1

공식 코드

Deep Reinforcement Learning for Producing Furniture Layout in Indoor Scenes

https://github.com/CODE-SUBMIT/simulator2

공식 코드

Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes

https://github.com/CORE-Robotics-Lab/ProLoNets

공식 코드

Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning

https://github.com/CPJKU/score_following_game

공식 코드

Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game

https://github.com/CPS-TUWien/racing_dreamer

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Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing

https://github.com/CR-Gjx/LeakGAN

공식 코드

Long Text Generation via Adversarial Training with Leaked Information

https://github.com/CVC-Lab/SAC-for-H-Bond-Learning

공식 코드

Reinforcement Learning for Molecular Dynamics Optimization: A Stochastic Pontryagin Maximum Principle Approach

https://github.com/CatIIIIIIII/veriseek

공식 코드

Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning

https://github.com/CatherineWong/dancin_seq2seq

공식 코드

DANCin SEQ2SEQ: Fooling Text Classifiers with Adversarial Text Example Generation

https://github.com/CausalML/DoubleReinforcementLearningMDP

공식 코드

Double Reinforcement Learning for Efficient Off-Policy Evaluation in Markov Decision Processes

https://github.com/CausalRL/DRL

공식 코드

Deconfounding Reinforcement Learning in Observational Settings

https://github.com/ChanganVR/RelationalGraphLearning

공식 코드

Relational Graph Learning for Crowd Navigation

https://github.com/CharlieLeeeee/TQPO

공식 코드

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning

https://github.com/Chenglin-Yang/PatchAttack

공식 코드

PatchAttack: A Black-box Texture-based Attack with Reinforcement Learning

https://github.com/ChienFeng-hub/meow

공식 코드

Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow

https://github.com/ChristosKap/multi_timescale_replay

공식 코드

Continual Reinforcement Learning with Multi-Timescale Replay

https://github.com/CoAxLab/azad

공식 코드

Combining imagination and heuristics to learn strategies that generalize

https://github.com/Collins-Ogbodo/DT-SS

공식 코드

Adaptive Sensor Steering Strategy Using Deep Reinforcement Learning for Dynamic Data Acquisition in Digital Twins

https://github.com/Confusezius/CVPR2020_PADS

공식 코드

PADS: Policy-Adapted Sampling for Visual Similarity Learning

https://github.com/CrickWu/Swtich-DDQ

공식 코드

Switch-based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning

https://github.com/D-X-Y/NAS-Projects

공식 코드

Searching for A Robust Neural Architecture in Four GPU Hours

https://github.com/DEAkimov/learn_to_move

공식 코드

Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation

https://github.com/DFKI-NLP/weak-supervision-rlhf

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Reward Modeling with Weak Supervision for Language Models

https://github.com/DIR-LAB/deep-batch-scheduler

공식 코드

RLScheduler: An Automated HPC Batch Job Scheduler Using Reinforcement Learning

https://github.com/DLR-RM/stable-baselines3

공식 코드

Smooth Exploration for Robotic Reinforcement Learning

https://github.com/DSS-lab/DRLCyberAssessment_DQNCode

공식 코드

Deep Reinforcement Learning for Cybersecurity Assessment of Wind Integrated Power Systems

https://github.com/DaRL-LibSignal/LibSignal

공식 코드

LibSignal: An Open Library for Traffic Signal Control

https://github.com/Dam930/rllab

공식 코드

Stochastic Variance-Reduced Policy Gradient

https://github.com/Damcy/cascadeLSTMDRL

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Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue

https://github.com/DanieleGammelli/gnn-rl-for-amod

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Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems

https://github.com/DarkDawn233/D2R_MTRL

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Not All Tasks Are Equally Difficult: Multi-Task Deep Reinforcement Learning with Dynamic Depth Routing

https://github.com/Dasudian/Curvetime

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Blockchain Framework for Artificial Intelligence Computation

https://github.com/DavidJanz/molecule_grammar_rnn

공식 코드

Learning a Generative Model for Validity in Complex Discrete Structures

https://github.com/DavidLeeftink/probabilistic-pontryagin-control

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Probabilistic Pontryagin's Maximum Principle for Continuous-Time Model-Based Reinforcement Learning

https://github.com/DeepGraphLearning/GraphAF

공식 코드

GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

https://github.com/Deepakgthomas/TSM_RL

공식 코드

Temporal Shift Reinforcement Learning

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