Sense-making via Collaborative Agents and Activity Networks (SCAAN)

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$150,000.00
Award Year:
2013
Program:
SBIR
Phase:
Phase I
Contract:
FA8750-13-C-0077
Agency Tracking Number:
O123-AU6-1130
Solicitation Year:
2012
Solicitation Topic Code:
OSD12-AU6
Solicitation Number:
2012.3
Small Business Information
Aptima, Inc.
12 Gill Street, Suite 1400, Woburn, MA, -
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
967259946
Principal Investigator:
Georgiy Levchuk
Simulation&Optimization Engineer
(781) 496-2467
georgiy@aptima.com
Business Contact:
Thomas McKenna
Chief Financial Officer
(781) 496-2443
mckenna@aptima.com
Research Institution:
n/a
Abstract
The quantity of data that need to be collected, examined and shared during Intelligence, Surveillance, and Reconnaissance Operations is growing fast due to increasing use of sensors. To deal with this challenge, the Air Force intelligence services are implementing a new process of planning and direction, collection, processing and exploitation, analysis and production, and dissemination (PCPAD). PCPAD requires new technologies that collect and process only the most critical and relevant information. Aptima proposes to develop a system for Sense-making via Collaborative Agents and Attributed Networks (SCAAN) that integrates distributed situation understanding, autonomous knowledge seeking, dynamic collaboration, and an adaptive heterogeneous command and control organization. SCAAN will solve challenges of collaborative large-scale information processing by incorporating a model of dependencies between essential elements of information based on real-world processes into its distributed information sharing framework. These dependencies will be used to construct an agent organization, which assigns command and execution roles to sensor nodes and is required for reducing complexity of managing heterogeneous sensor team, and a collaboration policy, which will be based on dependencies between the tasks executed by different nodes. SCAAN will achieve reduction in data analysis time while maintaining optimality of situation estimates obtained in a distributed manner.

* information listed above is at the time of submission.

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