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Proceedings Paper

Representation of potential information gain to measure the price of anarchy on ISR activities
Author(s): Hector J. Ortiz-Peña; Michael Hirsch; Mark Karwan; Rakesh Nagi; Moises Sudit
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Paper Abstract

One of the main technical challenges facing intelligence analysts today is effectively determining information gaps from huge amounts of collected data. Moreover, getting the right information to/from the right person (e.g., analyst, warfighter on the edge) at the right time in a distributed environment has been elusive to our military forces. Synchronization of Intelligence, Surveillance, and Reconnaissance (ISR) activities to maximize the efficient utilization of limited resources (both in quantity and capabilities) has become critically important to increase the accuracy and timeliness of overall information gain. Given this reality, we are interested in quantifying the degradation of solution quality (i.e., information gain) as a centralized system synchronizing ISR activities (from information gap identification to information collection and dissemination) moves to a more decentralized framework. This evaluation extends the concept of price of anarchy, a measure of the inefficiency of a system when agents maximize decisions without coordination, by considering different levels of decentralization. Our initial research representing the potential information gain in geospatial and time discretized spaces is presented. This potential information gain map can represent a consolidation of Intelligence Preparation of the Battlefield products as input to automated ISR synchronization tools. Using the coordination of unmanned vehicles (UxVs) as an example, we developed a mathematical programming model for multi-perspective optimization in which each UxV develops its own fight plan to support mission objectives based only on its perspective of the environment (i.e., potential information gain map). Information is only exchanged when UxVs are part of the same communication network.

Paper Details

Date Published: 28 May 2013
PDF: 11 pages
Proc. SPIE 8758, Next-Generation Analyst, 87580M (28 May 2013); doi: 10.1117/12.2015793
Show Author Affiliations
Hector J. Ortiz-Peña, CUBRC, Inc. (United States)
Michael Hirsch, Raytheon, Co. (United States)
Mark Karwan, Univ. at Buffalo (SUNY) (United States)
Rakesh Nagi, Univ. at Buffalo (SUNY) (United States)
Moises Sudit, CUBRC, Inc. (United States)

Published in SPIE Proceedings Vol. 8758:
Next-Generation Analyst
Barbara D. Broome; David L. Hall; James Llinas, Editor(s)

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