https://github.com/NeuroCSUT/DeepMind-Atari-Deep-Q-Learner-2Player
공식 코드Multiagent Cooperation and Competition with Deep Reinforcement Learning
Papers with Code 아카이브
Deep Reinforcement Learning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/NeuroCSUT/intentions
공식 코드https://github.com/NevVerVer/DBS-Gym
공식 코드https://github.com/Nick-Kou/RL-PGO
공식 코드RL-PGO: Reinforcement Learning-based Planar Pose-Graph Optimization
https://github.com/Nirnai/DeepRL
공식 코드https://github.com/Nordeus/heroic-rl
공식 코드https://github.com/Octavio-Pappalardo/Meta-learning-rewards
공식 코드Black box meta-learning intrinsic rewards for sparse-reward environments
https://github.com/OliverRichter/map-reader
공식 코드Teaching a Machine to Read Maps with Deep Reinforcement Learning
https://github.com/OptiMaL-PSE-Lab/CIRL
공식 코드Control-Informed Reinforcement Learning for Chemical Processes
https://github.com/OptimalPursuit/navigating_uncertainty_in_mpp
공식 코드https://github.com/OscarHuangWind/Preference-Guided-DQN-Atari
공식 코드Sampling Efficient Deep Reinforcement Learning through Preference-Guided Stochastic Exploration
https://github.com/PAL-ML/PEARL_v1
공식 코드https://github.com/PTF-transfer/Code_PTF
공식 코드Efficient Deep Reinforcement Learning via Adaptive Policy Transfer
https://github.com/PaddlePaddle/XWorld
공식 코드Guided Feature Transformation (GFT): A Neural Language Grounding Module for Embodied Agents
https://github.com/Pavan-Samtani/RLSoccer
공식 코드https://github.com/RL-WFU/Drone_field
공식 코드Deep Reinforcement Learning for Adaptive Exploration of Unknown Environments
https://github.com/RLGC-Project/RLGC
공식 코드Adaptive Power System Emergency Control using Deep Reinforcement Learning
https://github.com/Rhoban/footstepnet_envs
공식 코드https://github.com/RingBDStack/AR-DBSCAN
공식 코드Adaptive and Robust DBSCAN with Multi-agent Reinforcement Learning
https://github.com/Robinroy-peter/DRL-DynamicDroneLanding
공식 코드Lander.AI: Adaptive Landing Behavior Agent for Expertise in 3D Dynamic Platform Landings
https://github.com/RobustFieldAutonomyLab/DRL_graph_exploration
공식 코드Autonomous Exploration Under Uncertainty via Deep Reinforcement Learning on Graphs
https://github.com/RyanHaoranLi/CAR-RL
공식 코드Towards Optimal Adversarial Robust Reinforcement Learning with Infinity Measurement Error
https://github.com/SPEAR-IIT/CQSim
공식 코드https://github.com/SaeedTafazzol/curious_explorer
공식 코드Curious Exploration and Return-based Memory Restoration for Deep Reinforcement Learning
https://github.com/SarodYatawatta/smart-calibration
공식 코드Deep reinforcement learning for smart calibration of radio telescopes
https://github.com/SeldonIO/alibi
공식 코드Model-agnostic and Scalable Counterfactual Explanations via Reinforcement Learning
https://github.com/SenneDeproost/CM-GP
공식 코드Human-Readable Programs as Actors of Reinforcement Learning Agents Using Critic-Moderated Evolution
https://github.com/ShawK91/erl_paper_nips18
공식 코드https://github.com/Shawn-Guo-CN/EmergentNumerals
공식 코드Emergence of Numeric Concepts in Multi-Agent Autonomous Communication
https://github.com/Sheng-J/DOM-Q-NET
공식 코드https://github.com/ShengrenHou/Energy-management-MIP-Deep-Reinforcement-Learning
공식 코드Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm
https://github.com/Shuijing725/CrowdNav_DSRNN
공식 코드Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
https://github.com/Shuijing725/VAE_trait_inference
공식 코드Learning to Navigate Intersections with Unsupervised Driver Trait Inference
https://github.com/Skylark0924/Gamma_Reward
공식 코드Learning Scalable Multi-Agent Coordination by Spatial Differentiation for Traffic Signal Control
https://github.com/Sohojoe/ppo-dash
공식 코드PPO Dash: Improving Generalization in Deep Reinforcement Learning
https://github.com/SuerpX/Embedded-Self-Predictions
공식 코드Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.