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OpenAI Gym

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평가표: 17
보존된 평가 기록: 45

An open-source toolkit from OpenAI that implements several Reinforcement Learning benchmarks including: classic control, Atari, Robotics and MuJoCo tasks.

(Description by Evolutionary learning of interpretable decision trees)

(Image Credit: OpenAI Gym)

코드

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

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

Decision Transformer: Reinforcement Learning via Sequence Modeling

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

Continuous control with deep reinforcement learning

https://github.com/SPark9625/PyTorch-Proximal-Policy-Optimization

Proximal Policy Optimization Algorithms

https://github.com/SalvatoreCognetta/reasoning-agent-project

Proximal Policy Optimization Algorithms

https://github.com/SaminYeasar/off_policy_ac

Continuous control with deep reinforcement learning

https://github.com/SergiPonsa/Reinforcement-Learning-Sergi

Continuous control with deep reinforcement learning

https://github.com/SeungeonBaek/continuous-agents-test

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/ShawK91/Evolutionary-Reinforcement-Learning

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

https://github.com/ShawK91/erl_paper_nips18

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

https://github.com/Sheldonmao/Learning-To-walk

Continuous control with deep reinforcement learning

https://github.com/SimonRamstedt/ddpg

Continuous control with deep reinforcement learning

https://github.com/Souphis/mobile_robot_rl

Continuous control with deep reinforcement learning

https://github.com/Steinheilig/Imbiss

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

https://github.com/Steve--Hunter/gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/Stippler/cow-simulator

Proximal Policy Optimization Algorithms

https://github.com/T3chy/DDPG

Continuous control with deep reinforcement learning

https://github.com/TheInfamousWayne/ddpg

Continuous control with deep reinforcement learning

https://github.com/TobiKick/DL_LF2

Deep Reinforcement Learning for Playing 2.5D Fighting Games

https://github.com/UesugiErii/tf2-PPO-atari

Proximal Policy Optimization Algorithms

https://github.com/VasaKiDD/TD3-deep-rl-research

Continuous control with deep reinforcement learning

https://github.com/WittmannF/quadcopter-best-practices

Continuous control with deep reinforcement learning

https://github.com/X3N4/car_racer

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

https://github.com/YYCAAA/V-MPO_Lunarlander

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

https://github.com/YangRui2015/Modular_HER

Continuous control with deep reinforcement learning

https://github.com/YanglanWang/classic_control

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/YoUNG824/DDPG

Continuous control with deep reinforcement learning

https://github.com/ZainRaza14/deepRL

Continuous control with deep reinforcement learning

https://github.com/Zartris/TD3_continuous_control

Proximal Policy Optimization Algorithms

https://github.com/ZiyangY/IndProject-RL-in-Supply-chain

Continuous control with deep reinforcement learning

https://github.com/a-ozeki/openAI_gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/abbadka/quadcopter

Continuous control with deep reinforcement learning

https://github.com/abhiksingla/gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/ac-93/soft-actor-critic

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

https://github.com/acht7111020/DRL-playing-2.5D-fighting-game

Deep Reinforcement Learning for Playing 2.5D Fighting Games

https://github.com/acyclics/MPO

Relative Entropy Regularized Policy Iteration

https://github.com/adamos581/ppo-keras-football

Proximal Policy Optimization Algorithms

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