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Dota 2
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Dota 2 is a multiplayer online battle arena (MOBA). The task is to train one-or-more agents to play and win the game.
<span style="color:grey; opacity: 0.6">( Image credit: OpenAI Five )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/InSpaceAI/RL-Zoo
https://github.com/Ipsedo/EvoMotion
https://github.com/JL321/Proximal-Policy-Optimization
https://github.com/JonasRSV/PPO
https://github.com/Khrylx/PyTorch-RL
https://github.com/LuEE-C/PPO-Keras
https://github.com/MatteoBrentegani/PPO
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Proximal_Policy_Optimization_Algorithms
https://github.com/Michaelrising/Prog-RL
https://github.com/MrSyee/pg-is-all-you-need
https://github.com/NACLab/robust-active-inference
https://github.com/Narsil/rl-baselines
https://github.com/NervanaSystems/coach
https://github.com/Nordeus/heroic-rl
https://github.com/OctThe16th/PPO-Keras
https://github.com/OctopusMind/RLHF_PPO
https://github.com/Ostyk/walk-bot
https://github.com/Rafael1s/Deep-Reinforcement-Learning-Udacity
https://github.com/RexGLiu/rlpyt_crbp
https://github.com/SPark9625/PyTorch-Proximal-Policy-Optimization
https://github.com/SalvatoreCognetta/reasoning-agent-project
https://github.com/Stippler/cow-simulator
https://github.com/UesugiErii/tf2-PPO-atari
https://github.com/Zartris/TD3_continuous_control
https://github.com/adamos581/ppo-keras-football
https://github.com/adik993/ppo-pytorch
https://github.com/ailab-pku/rl-framework
https://github.com/akterskii/rlpyt
https://github.com/alecfilios/Training-Intelligent-game-Agents-through-Competitive-Reinforcement-Learning
https://github.com/alex-petrenko/sample-factory
https://github.com/alexbaumi/PPO-Algorithm
https://github.com/alexbaumi/PPO-Algorithms
https://github.com/alexmlamb/blocks_rl_gru_setup
https://github.com/alexsax/testing_rlpyt
https://github.com/alirezakazemipour/ppo-rnd
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.