Hierarchical Reinforcement Learning for Multi-agent MOBA Game

Real Time Strategy (RTS) games require macro strategies as well as micro strategies to obtain satisfactory performance since it has large state space, action space, and hidden information. This paper presents a novel hierarchical reinforcement learning model for mastering Multiplayer Online Battle A...

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Veröffentlicht in:	arXiv.org 2019-06
Hauptverfasser:	Zhang, Zhijian, Li, Haozheng, Zhang, Luo, Zheng, Tianyin, Zhang, Ting, Xiong Hao, Chen, Xiaoxin, Chen, Min, Xiao, Fangxu, Zhou, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer & video games Feature extraction Game theory Machine learning Mastering Multiagent systems Target detection
Online-Zugang:	Volltext
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