Multi-agent deep reinforcement learning using attentive graph neural architectures for real-time strategy games

WJ Yun, S Yi, J Kim - … on Systems, Man, and Cybernetics (SMC), 2021 - ieeexplore.ieee.org
In real-time strategy (RTS) game artificial intelligence research, various multi-agent deep
reinforcement learning (MADRL) algorithms are widely and actively used nowadays. Most of …
被引用次数：12 相关文章

Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games

WJ Yun, S Yi, J Kim - 2021 IEEE International Conference on Systems …, 2021 - dl.acm.org
In real-time strategy (RTS) game artificial intelligence research, various multi-agent deep
reinforcement learning (MADRL) algorithms are widely and actively used nowadays. Most of …

Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games

WJ Yun, S Yi, J Kim - arXiv preprint arXiv:2105.10211, 2021 - arxiv.org
In real-time strategy (RTS) game artificial intelligence research, various multi-agent deep
reinforcement learning (MADRL) algorithms are widely and actively used nowadays. Most of …

Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games

WJ Yun, S Yi, J Kim - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
In real-time strategy (RTS) game artificial intelligence research, various multi-agent deep
reinforcement learning (MADRL) algorithms are widely and actively used nowadays. Most of …