Fuzzy Reinforcement Learning for System of Systems (SOS)

被引：0

作者：

Berenji, Hamid ^{[1
]}

Jamshidi, Mo ^{[2
]}

机构：

[1] IIS Corp, MS 566-108,NASA Res Pk, Moffett Field, CA 94035 USA

[2] Univ Texas San Antonio, ACE Ctr, ECEC Dept, San Antonio, TX 78249 USA

来源：

IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ 2011) | 2011年

关键词：

System of Systems (SOS); Fuzzy Reinforcement Learning (FRL); robots; cooperation; Unmanned Ground Vehicles (UGVs);

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The System of Systems (SOS) technology is an advanced technology for Intelligent Systems that is developed with multiple intelligent systems. Recently, there has been a growing interest in a class of complex systems (robotic swarm as an example) whose constituents are themselves complex. Performance optimization, robustness and reliability among an emerging group of heterogeneous systems in order to realize a common goal have become the focus of various applications including military, security, aerospace, space, manufacturing, service industry, environmental systems, and disaster management, to name a few. In this paper, we discuss how Fuzzy Reinforcement Learning (FRL) can be used in SOS.

引用

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页码：1689 / 1694

页数：6

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