Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management

Andrew J. Newman; Casey L. Richardson; Sean M. Kain; Paul G. Stankiewicz; Paul R. Guseman; Blake A. Schreurs; Jeffrey A. Dunne

doi:10.1117/12.2228127

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17 May 2016 Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management

Andrew J. Newman, Casey L. Richardson, Sean M. Kain, Paul G. Stankiewicz, Paul R. Guseman, Blake A. Schreurs, Jeffrey A. Dunne

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Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 984209 (2016) https://doi.org/10.1117/12.2228127
Event: SPIE Defense + Security, 2016, Baltimore, Maryland, United States

Abstract

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.

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Andrew J. Newman, Casey L. Richardson, Sean M. Kain, Paul G. Stankiewicz, Paul R. Guseman, Blake A. Schreurs, and Jeffrey A. Dunne "Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 984209 (17 May 2016); https://doi.org/10.1117/12.2228127

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