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Reinforcement Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kjboggess/ijcai23
공식 코드Explainable Multi-Agent Reinforcement Learning for Temporal Queries
https://github.com/kngwyu/rogue-gym
공식 코드Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning
https://github.com/kngwyu/rogue-gym-agents-cog19
공식 코드Rogue-Gym: A New Challenge for Generalization in Reinforcement Learning
https://github.com/knowledgedefinednetworking/DRL-GNN
공식 코드Deep Reinforcement Learning meets Graph Neural Networks: exploring a routing optimization use case
https://github.com/knowledgetechnologyuhh/goal_conditioned_RL_baselines
공식 코드https://github.com/knowledgetechnologyuhh/hipss
공식 코드Grounding Hindsight Instructions in Multi-Goal Reinforcement Learning for Robotics
https://github.com/kogler7/aoiopt
공식 코드DRL4AOI: A DRL Framework for Semantic-aware AOI Segmentation in Location-Based Services
https://github.com/konatanaya/geometric-actor-critic
공식 코드GAC: A Deep Reinforcement Learning Model Toward User Incentivization in Unknown Social Networks
https://github.com/kramerlab/peerlearning
공식 코드Peer Learning: Learning Complex Policies in Groups from Scratch via Action Recommendations
https://github.com/kristian-georgiev/sgmrl
공식 코드On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement Learning
https://github.com/krystalan/drt
공식 코드https://github.com/krzentner/language-world
공식 코드Conditionally Combining Robot Skills using Large Language Models
https://github.com/kschmeckpeper/rl_with_videos
공식 코드Reinforcement Learning with Videos: Combining Offline Observations with Interaction
https://github.com/ksenia-konyushkova/LAL-RL
공식 코드https://github.com/kth-flowai/advanceddeepreinforcementlearning_rbc_control
공식 코드https://github.com/kth-flowai/deepreinforcementlearning_rayleighbenard2d_control
공식 코드https://github.com/kth-flowai/drl_marl_rayleighbenard3d_control
공식 코드Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection
https://github.com/kuangqi927/qem
공식 코드https://github.com/kurayuri/reinfier
공식 코드https://github.com/kvablack/ddpo-pytorch
공식 코드https://github.com/kvfrans/fre
공식 코드Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
https://github.com/kwai/DouZero
공식 코드DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning
https://github.com/kzbikowski/ProcessGym
공식 코드Deep Reinforcement Learning for Resource Allocation in Business Processes
https://github.com/kzl/aop
공식 코드https://github.com/kzl/decision-transformer
공식 코드Decision Transformer: Reinforcement Learning via Sequence Modeling
https://github.com/lace-lab/bounding-box
공식 코드Bounding-Box Inference for Error-Aware Model-Based Reinforcement Learning
https://github.com/lamda-bbo/macro-regulator
공식 코드Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer
https://github.com/lamda-rl/gentle
공식 코드https://github.com/lamda-rl/imaginebench
공식 코드ImagineBench: Evaluating Reinforcement Learning with Large Language Model Rollouts
https://github.com/lamda-rl/prdc
공식 코드Policy Regularization with Dataset Constraint for Offline Reinforcement Learning
https://github.com/lamsieh/DQN
공식 코드Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection
https://github.com/lancopku/Skeleton-Based-Generation-Model
공식 코드A Skeleton-Based Model for Promoting Coherence Among Sentences in Narrative Story Generation
https://github.com/lancopku/unpaired-sentiment-translation
공식 코드Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach
https://github.com/lanyavik/BAIL
공식 코드BAIL: Best-Action Imitation Learning for Batch Deep Reinforcement Learning
https://github.com/lara-martin/StoryPlot-RewardShaping
공식 코드Controllable Neural Story Plot Generation via Reward Shaping
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.