Reconnaissance Blind Multi-Chess: An Experimentation Platform for ISR Sensor Fusion and Resource Management

被引:3
|
作者
Newman, Andrew J. [1 ]
Richardson, Casey L. [1 ]
Kain, Sean M. [1 ]
Stankiewicz, Paul G. [1 ]
Guseman, Paul R. [1 ]
Schreurs, Blake A. [1 ]
Dunne, Jeffrey A. [1 ]
机构
[1] Johns Hopkins Univ, Appl Phys Lab, 11100 Johns Hopkins Rd, Laurel, MD 20723 USA
关键词
Chess; Kriegspiel; Decision Making Under Uncertainty; Stochastic Control; Sensor Fusion; Sensor Resource Management; ISR; Intelligent Systems; KRIEGSPIEL; GO;
D O I
10.1117/12.2228127
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper introduces the game of reconnaissance blind multi-chess (RBMC) as a paradigm and test bed for understanding and experimenting with autonomous decision making under uncertainty and in particular managing a network of heterogeneous Intelligence, Surveillance and Reconnaissance (ISR) sensors to maintain situational awareness informing tactical and strategic decision making. The intent is for RBMC to serve as a common reference or challenge problem in fusion and resource management of heterogeneous sensor ensembles across diverse mission areas. We have defined a basic rule set and a framework for creating more complex versions, developed a web-based software realization to serve as an experimentation platform, and developed some initial machine intelligence approaches to playing it.
引用
收藏
页数:20
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