Papers with Code 아카이브
Real-Time Strategy Games
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Real-Time Strategy (RTS) tasks involve training an agent to play video games with continuous gameplay and high-level macro-strategic goals such as map control, economic superiority and more.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-platform Version of StarCraft: Brood War in a Docker Container )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/raccoon831012/StartCraft2-RL
https://github.com/ray-project/ray/tree/master/rllib
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
https://github.com/sagpant/TorchCraft
TorchCraft: a Library for Machine Learning Research on Real-Time Strategy Games
https://github.com/shariqiqbal2810/AI-QMIX
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
https://github.com/simsimiSION/pymarl-algorithm-extension-via-starcraft
https://github.com/sjtu-marl/bd_rd_psro
https://github.com/smerdov/DataCollectionSystem
https://github.com/starry-sky6688/marl-algorithms
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
https://github.com/sunjing1102628/DOMAC
https://github.com/tencent-ailab/Arena
https://github.com/tjuhaoxiaotian/pymarl3
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
https://github.com/tumcps/commonpower
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
https://github.com/tuomaso/SC2LE-implementation
https://github.com/ucl-dark/pax
https://github.com/umersheikh846/WQMIX
https://github.com/universome/stylegan-v
Towards Accurate Generative Models of Video: A New Metric & Challenges
https://github.com/uoe-agents/epymarl
https://github.com/wilson1yan/VideoGPT
Towards Accurate Generative Models of Video: A New Metric & Challenges
https://github.com/xiuyu0000/new_papers_codes/tree/main/mappo
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
https://github.com/xiuyu0000/new_papers_codes/tree/main/qmix
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
https://github.com/zoeyuchao/mappo
The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.