Distributed multi-agent deep reinforcement learning for cooperative multi-robot pursuit

As a popular research topic in the area of distributed artificial intelligence, the multi-robot pursuit problem is widely used as a testbed for evaluating coordinated and cooperative strategies in multi-robot systems. This study the problem of multi-robot pursuit game using reinforcement learning (R...

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Veröffentlicht in:	Journal of engineering (Stevenage, England) Jg. 2020; H. 13; S. 499 - 504
Hauptverfasser:	Yu, Chao, Dong, Yinzhao, Li, Yangning, Chen, Yatong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	The Institution of Engineering and Technology 01.07.2020
Schlagworte:	control engineering computing decentralised‐execution scheme deep RL methods distributed artificial intelligence distributed control distributed multiagent deep reinforcement learning environmental agents game theory individual action output individual leaning update process learning (artificial intelligence) learning systems multiagent deep RL approach multirobot pursuit game multirobot systems multi‐agent systems multi‐robot systems pursuit‐evasion problem The 3rd Asian Conference on Artificial Intelligence Technology (ACAIT 2019) pursuit-evasion problem multi-agent systems individual leaning update process distributed control game theory multirobot pursuit game deep RL methods multi-robot systems decentralised-execution scheme distributed artificial intelligence learning systems environmental agents individual action output distributed multiagent deep reinforcement learning multiagent deep RL approach learning (artificial intelligence) control engineering computing multirobot systems
ISSN:	2051-3305, 2051-3305
Online-Zugang:	Volltext
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