SBIR/STTR Research Award

Game Theoretic Multi-agent Modeling and Analysis Framework for Distributed Collaborative Systems with Aid of Data Mining and Data Fusion

Award identifier 6bde3e1dd200328dfa1150772d86df281709c87edcd7318491d02e6fef306e0aAwarding agency Department of Defense · Air Force

Award amount

$100,000

Program and phase

SBIR · Phase I

Award year

2008

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
DCM Research Resources, LLC
Proposal award date
2008-06-19
Contract end date
2009-05-11
UEI
CYLLWBAP3RK9
Solicitation number
2008.1
Topic code
AF081-096

Research abstract

We propose a highly innovative modeling and analysis framework for distributed collaborative systems with aid of data-mining and data-fusion concept. Our approach has two major highly coupled parts: 1) Data fusion module. Mutliple-sensor data are fused to perform situation awareness. To generate the intent inference of the targets, we will extend Markov games via incorporating Multi-Cumulant Pareto Nash strategies and Graph concept. From a perspective of distributed decision making problem, we dynamically adapt Hierarchical Task Network and Auction algorithm for optimal meta-task decomposition and assignment. A collaborative search and tracking oriented sensor management algorithm based on Pursuit-Evasion game will be exploited to improve the performance of the multi-layered sensing system. 2) Data-mining module. Adaptation and pattern/feature recognition are carried out to dynamically select (or mine) appropriate features or feature sets and quickly associate them with the adversary intent and executable actions. In some time-critical scenarios, firstly, a primitive adversary intent estimation and the associated friendly force collaborative response actions can be quickly provided by the Data-mining module. Then, a refinement based on data-fusion will be carried out to improve the performance of the decision aids tool. Additionally, we will incorporate a semantic and textual processing technique to convert meta-tasks into actionable fusion processes BENEFIT: The proposed game theoretic decision aid tool for cooperative system modeling, simulation, and analysis has tremendous applications potential in many military applications. It can also be directly used for developing of advanced mission planning and emergency preparedness decision support systems such as Space Situational Awareness Fusion Intelligent Research Environment [SAFIRE] program, BMDS system, Future Combat System (FCS), Joint Strike Fighter (JSF) program, JSSEO program, and AEGIS program. DCM and Lockheed Martin are building a mentor-protégé program. We will leverage this relationship to identify the end customer, and work with these teams to transition our technoloy into their program. The DOD contact who knows the details of our work and who knows the above programs is Dr. Erik Blasch from AFRL. Other potential commercial applications include inter-satellite communications, multi-layered sensing, disaster assessment, air traffic control system, the national weather service, physical security systems, law enforcement agency, emergency control center, border and coast patrol, pollution monitoring, remote sensing and global awareness. We expect the aggregated market size will be similar to that of military applications.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

7 SBIR/STTR records share this UEI (2008–2010). Reported award amounts total $1,979,149. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense

Agency intelligence

Department of Defense

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