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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/KodirjonAkhmedov/Real-Time-Data-Collection-Dota-2
공식 코드https://github.com/adam-katona/dota2_death_prediction
공식 코드https://github.com/chitaapc/dota2_beyondthemeta_characterrepresentation
공식 코드Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analytics
https://github.com/chitaapc/dota2ccr
공식 코드Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analytics
https://github.com/facebookresearch/CollaQ
공식 코드Multi-Agent Collaboration via Reward Attribution Decomposition
https://github.com/ml-jku/helm
공식 코드Semantic HELM: A Human-Readable Memory for Reinforcement Learning
https://github.com/tencent-ailab/tleague_projpage
공식 코드TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
https://github.com/ubiquition/drl
공식 코드https://github.com/ubisoft/ubisoft-laforge-toxbuster
공식 코드Towards Detecting Contextual Real-Time Toxicity for In-Game Chat
https://bitbucket.org/act-lab/release
https://github.com/170928/-Review-Generative-Adversarial-Imitation-Learning
https://github.com/170928/-Review-Proximal-Policy-Optimization-Algorithms
https://github.com/2mawi2/master-thesis-experiments
https://github.com/ASzot/ppo-pytorch
https://github.com/Aravind-11/AI-Gaming
https://github.com/Aravind-11/IITM_Saastra
https://github.com/Aravind-11/Multi-Agent-RL
https://github.com/BIT-aerial-robotics/AquaML/blob/2.1.11/AquaML/rlalgo/PPOAgent.py
https://github.com/BerkeleyLearnVerify/VerifAI
https://github.com/BrianPulfer/PapersReimplementations
https://github.com/CSautier/Breakout
https://github.com/CSautier/PongBot
https://github.com/Crevass/Hybrid-Agent
https://github.com/DLR-RM/stable-baselines3
https://github.com/DMIU-ShELL/MOSAIC
https://github.com/DanyWind/fastai_bs_finder
https://github.com/DavidCastilloAlvarado/Path-planning-and-Reinforcement-Learning
https://github.com/DevSlem/AINE-DRL
https://github.com/EconomistGrant/HTFE-tensortrade
https://github.com/FMArduini/python-rl
https://github.com/GiadaSimionato/Reasoning_Agents_2020
https://github.com/Gouet/Acrobot-PPO
https://github.com/Gouet/Breakout-V0
https://github.com/Gouet/PPO-gym
https://github.com/Gouet/PPO-pytorch
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.