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

https://github.com/MrSyee/pg-is-all-you-need

Proximal Policy Optimization Algorithms

https://github.com/N0r9st/a2c-jax

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/NACLab/robust-active-inference

Proximal Policy Optimization Algorithms

https://github.com/Narsil/rl-baselines

Proximal Policy Optimization Algorithms

https://github.com/Nasdin/ReinforcementLearning-AtariGame

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/NervanaSystems/coach

Playing Atari with Deep Reinforcement Learning

https://github.com/NikolausBerl/Udacity_DRLN_Navigation_Project

Deep Reinforcement Learning with Double Q-learning

https://github.com/NinaPi/Lunar_Causal_Network

Explainable Reinforcement Learning Through a Causal Lens

https://github.com/Nkluge-correa/teeny-tiny_castle

Agent57: Outperforming the Atari Human Benchmark

https://github.com/Nordeus/heroic-rl

Proximal Policy Optimization Algorithms

https://github.com/OMS1996/Carla_The_RL_Self-Driving-Car

Deep Reinforcement Learning with Double Q-learning

https://github.com/OctThe16th/PPO-Keras

Proximal Policy Optimization Algorithms

https://github.com/OctopusMind/RLHF_PPO

Proximal Policy Optimization Algorithms

https://github.com/Ostyk/walk-bot

Proximal Policy Optimization Algorithms

https://github.com/PCJohn/cata-forget

Overcoming catastrophic forgetting in neural networks

https://github.com/PaulCharnay/Projet_AIF

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/PeterJochem/Deep_RL

Deep Reinforcement Learning with Double Q-learning

https://github.com/PeterJochem/Double_Deep_QLearning

Deep Reinforcement Learning with Double Q-learning

https://github.com/R-Stefano/DQN

Playing Atari with Deep Reinforcement Learning

https://github.com/R-Sweke/DeepQ-Decoding

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/RENHANFEI/patch_sup

Playing FPS Games with Deep Reinforcement Learning

https://github.com/RENHANFEI/vizdoom_health_gathering

Playing FPS Games with Deep Reinforcement Learning

https://github.com/RENHANFEI/vizdoom_patch_dqn

Playing FPS Games with Deep Reinforcement Learning

https://github.com/RENHANFEI/vizdoom_patch_supreme

Playing FPS Games with Deep Reinforcement Learning

https://github.com/RESQUELAB/RL-Teacher-UIAdaptation

Deep reinforcement learning from human preferences

https://github.com/RL-WFU/IC3Net-Highway

Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks

https://github.com/RLAgent/state-marginal-matching

Unifying Count-Based Exploration and Intrinsic Motivation

https://github.com/RLeike/connect-four

Playing Atari with Deep Reinforcement Learning

https://github.com/Rabrg/dqn

Playing Atari with Deep Reinforcement Learning

https://github.com/Rafael1s/Deep-Reinforcement-Learning-Udacity

Proximal Policy Optimization Algorithms

https://github.com/RajGhugare19/dreamerv2

Mastering Atari with Discrete World Models

https://github.com/RamiSketcher/decision-transformer-ammi

Decision Transformer: Reinforcement Learning via Sequence Modeling

https://github.com/RandyDeng/gym_connect4

Playing Atari with Deep Reinforcement Learning

https://github.com/Remtasya/DDPG-Actor-Critic-Reinforcement-Learning-Reacher-Environment

Prioritized Experience Replay

https://github.com/RevanMacQueen/LearningFromHumans

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

https://github.com/RexGLiu/rlpyt_crbp

Accelerated Methods for Deep Reinforcement Learning

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