Papers with Code 아카이브

Q-Learning

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The goal of Q-learning is to learn a policy, which tells an agent what action to take under what circumstances.

<span style="color:grey; opacity: 0.6">( Image credit: Playing Atari with Deep Reinforcement Learning )</span>

코드

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

https://github.com/EyaRhouma/collaboration-competition-MADDPG

Continuous control with deep reinforcement learning

https://github.com/FOCAL-ICLR/FOCAL-ICLR

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/FaboNo/DRLND

Deep Reinforcement Learning with Double Q-learning

https://github.com/FauzaanQureshi/deep-Q-learning

Playing Atari with Deep Reinforcement Learning

https://github.com/FlixCoder/rust-es-optimizer

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/FlyienSHaDOw/continuous_control

Continuous control with deep reinforcement learning

https://github.com/FlyienSHaDOw/project_2_continuous_control

Continuous control with deep reinforcement learning

https://github.com/Frager/Deep-Neuroevolution-In-SC2LE

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning

https://github.com/FrankPortman/stannis

Monte Carlo Q-learning for General Game Playing

https://github.com/Gary-Shi/Tank

Playing Atari with Deep Reinforcement Learning

https://github.com/GauravPatel89/Car-Navigation-Simulation-using-TD3

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/GhadaSokar/Dynamic-Sparse-Training-for-Deep-Reinforcement-Learning

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/Gouet/DDPG_PendulumV1

Continuous control with deep reinforcement learning

https://github.com/HanbumKo/distributed-wqmix

Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

https://github.com/HussonnoisMaxence/RL_Algorithms

Deep Reinforcement Learning with Double Q-learning

https://github.com/Improbable-AI/curiosity_baselines

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

https://github.com/InSpaceAI/RL-Zoo

Playing Atari with Deep Reinforcement Learning

https://github.com/Ipsedo/EvoMotion

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/Ishan-Kumar2/Reinforcement-Learning-on-2048

Playing Atari with Deep Reinforcement Learning

https://github.com/IvanVigor/Deep-Deterministic-Policy-Gradient-Unity-Env

Continuous control with deep reinforcement learning

https://github.com/IvanVigor/MADDPG-Unity

Continuous control with deep reinforcement learning

https://github.com/J93T/TP4-DDPG

Continuous control with deep reinforcement learning

https://github.com/JL321/mujo-2DHalf-Cheetah

Continuous control with deep reinforcement learning

https://github.com/JL321/mujo-2DWalker

Continuous control with deep reinforcement learning

https://github.com/JackFurby/Breakout

Playing Atari with Deep Reinforcement Learning

https://github.com/JayLohokare/taxi-v2

Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition

https://github.com/JinTanda/MADDPG_env

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/Joearrowsmith/hackcambridge_2020

Deep Recurrent Q-Learning for Partially Observable MDPs

https://github.com/Jogima-cyber/portfolio-manager

An intelligent financial portfolio trading strategy using deep Q-learning

https://github.com/JohannesAck/MATD3implementation

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/JohannesAck/tf2multiagentrl

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/JonasRSV/DDPG

Continuous control with deep reinforcement learning

https://github.com/JonasRSV/DQN

Playing Atari with Deep Reinforcement Learning

https://github.com/JonasRSV/DQNTensorflow

Playing Atari with Deep Reinforcement Learning

https://github.com/JonasRSV/PGTensorflow

Continuous control with deep reinforcement learning

https://github.com/JorgeA-RD/Reinforcement-Learning-Agents/tree/main/DDPG

Continuous control with deep reinforcement learning

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