OpenAI Gym
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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/gaetanserre/l2rpn-2022_ppo-baseline
https://github.com/garyzyr001/rethinking-airl
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/georgesung/TD3
Addressing Function Approximation Error in Actor-Critic Methods
https://github.com/georgkruse/cleanqrl
https://github.com/ghliu/pytorch-ddpg
https://github.com/gijskoning/ReproducingCURL
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/gmoss1/Kaggle-Halite-IV-RL
https://github.com/goncharom/PPOv1
https://github.com/google/trax
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
https://github.com/gstoica27/cpg_ppo
https://github.com/gtrll/dartenv
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
https://github.com/guillaumeboniface/reacher
https://github.com/guofeng201507/ISA-IPA-2020-05-05-IS1PT-GRP-High5-StockTrading
https://github.com/gwthomas/gtml
https://github.com/h-aboutalebi/SparceReward
https://github.com/halajadallah/RL-Quadcopter_project
https://github.com/hamishs/JAX-RL
https://github.com/harruff/Senior_Project_Repository
https://github.com/hcch0912/gym_wrapper_dm_soccer
https://github.com/hdparks/AsteroidsDeepReinforcement
https://github.com/hemilpanchiwala/Hindsight-Experience-Replay
https://github.com/heysoos/CriticalForagingOrgs
https://github.com/heysoos/critical-ising-evolution
https://github.com/hill-a/stable-baselines
https://github.com/hmhuy0/SIM-RL
https://github.com/hyerinshelly/RL_COVID-19_Korea
EpidemiOptim: A Toolbox for the Optimization of Control Policies in Epidemiological Models
https://github.com/hyunin-lee/ForecasterSAC
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/iDataist/Continuous-Control-with-Deep-Deterministic-Policy-Gradient
https://github.com/iDataist/Tennis-With-Multi-Agent-Reinforcement
https://github.com/ifestus/rl
https://github.com/ikostrikov/jax-rl
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
https://github.com/ikostrikov/pytorch-a2c-ppo-acktr-gail
https://github.com/ikostrikov/pytorch-rl
https://github.com/inoryy/reaver
https://github.com/intellisys-lab/stellaris-sc24
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.