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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/sparkmxy/my-offlinerl

Conservative Q-Learning for Offline Reinforcement Learning

https://github.com/spragunr/deep_q_rl

Playing Atari with Deep Reinforcement Learning

https://github.com/sreejeetm1729/Robust-Q-Learning-under-Corrupted-Rewards

Robust Q-Learning under Corrupted Rewards

https://github.com/ssainz/reinforcement_learning_algorithms

Deep Reinforcement Learning with Double Q-learning

https://github.com/starry-sky6688/MADDPG

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

https://github.com/stavrosgreece/MultiAgentLearning

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/stevenpjg/ddpg-aigym

Continuous control with deep reinforcement learning

https://github.com/subhadip-maiti/tinydqn

Playing Atari with Deep Reinforcement Learning

https://github.com/sufengniu/GVIN

Generalized Value Iteration Networks: Life Beyond Lattices

https://github.com/sunfex/weighted-sac

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

https://github.com/sunjeet95/Deep-Q-Network-using-Tensorflow

Playing Atari with Deep Reinforcement Learning

https://github.com/susan-amin/SparseBaseline1

Continuous control with deep reinforcement learning

https://github.com/susanwe/ope_worldmodels

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/suyoung-lee/Episodic-Backward-Update

Learning to Play in a Day: Faster Deep Reinforcement Learning by Optimality Tightening

https://github.com/sygi/deep_q_rl

Playing Atari with Deep Reinforcement Learning

https://github.com/taku-y/20181125-pybullet

Continuous control with deep reinforcement learning

https://github.com/tangxiangru/RL-for-RNA-design

Optimization of Molecules via Deep Reinforcement Learning

https://github.com/tarod13/SAC

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

https://github.com/tcmxx/CNTKUnityTools

Playing Atari with Deep Reinforcement Learning

https://github.com/tegg89/DLCamp_Jeju2018

Continuous control with deep reinforcement learning

https://github.com/tegg89/magnet

Continuous control with deep reinforcement learning

https://github.com/tegg89/magnn

Continuous control with deep reinforcement learning

https://github.com/tegg89/mann

Continuous control with deep reinforcement learning

https://github.com/tensorlayer/RLzoo

Continuous control with deep reinforcement learning

https://github.com/tensorpack/tensorpack/tree/master/examples/DeepQNetwork

Playing Atari with Deep Reinforcement Learning

https://github.com/tenvinc/CS4246-Project

Deep Q-learning from Demonstrations

https://github.com/thainv0212/re-ddpg

Continuous control with deep reinforcement learning

https://github.com/thechrisyoon08/Multi-agent-reinforcement-learning

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

https://github.com/thechrisyoon08/marl

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

https://github.com/theneuralbeing/neuroevolution

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

https://github.com/thomashirtz/pytorch-soft-actor-critic

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

https://github.com/thomashirtz/soft-actor-critic

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

https://github.com/thxsxth/POMDP_RLSepsis

Benchmarking Batch Deep Reinforcement Learning Algorithms

https://github.com/tilkb/thermoai

Continuous control with deep reinforcement learning

https://github.com/timoklein/car_racer

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

https://github.com/tkarr21/multagent-particle-envs

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

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