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Proceedings Paper

Reconnaissance blind multi-chess: an experimentation platform for ISR sensor fusion and resource management
Author(s): 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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Paper 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.

Paper Details

Date Published: 17 May 2016
PDF: 20 pages
Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 984209 (17 May 2016); doi: 10.1117/12.2228127
Show Author Affiliations
Andrew J. Newman, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Casey L. Richardson, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Sean M. Kain, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Paul G. Stankiewicz, Johns Hopkins Univ. Applied Physics Lab, LLC (United States)
Paul R. Guseman, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Blake A. Schreurs, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)
Jeffrey A. Dunne, Johns Hopkins Univ. Applied Physics Lab., LLC (United States)


Published in SPIE Proceedings Vol. 9842:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXV
Ivan Kadar, Editor(s)

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