SBIR/STTR Research Award

A Hybrid Architecture Approach to Forecasting Adversary Reactions

Award identifier 3755491efdd18808ea0dbb2624c0179823481046fd07394cec2fa5b4673a9098Awarding agency Department of Defense · Air Force

Award amount

$99,999

Program and phase

SBIR · Phase I

Award year

2009

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
SECURBORATION, INC.
Proposal award date
2009-02-10
Contract end date
2010-02-09
UEI
KMW3TK51HPN9
Solicitation number
2008.3
Topic code
AF083-058

Research abstract

Course of action (COA) analysis, especially adversary reaction prediction, that occurs during the Joint Operation Planning Process/Joint Air Estimate Process (JOPP/JAEP) has benefited by applying advanced computing algorithms. Typically though, algorithms have been narrowly applied to solve niche issues within broader JOPP/JAEP tasks. The concept of hybrid architectures seeks to provide a more holistic approach. With hybrid architectures, tasks are decomposed into subtasks that are assigned an algorithm suitable to performing that subtask. Hybrid architectures may be constructed from a variety of algorithms, and typically multiple algorithms can be applied to a general classification of problem. However, although the classification may be similar, the problem constraints imposed by the current situation in which decisions must be made vary greatly. To address these challenges, Securboration is teaming with artificial intelligence expert Dr. Eugene Santos from Dartmouth College to develop the Virtual Hybrid Architecture Computing System or VHACS. In Phase I of this effort, the Securboration Team will develop the VHACS prototype that determines appropriate algorithms to satisfy given subtasks within the current operational environment and then composes them into a specification that it invokes for a distributed execution. VHACS combines the benefits of traditional hybrid architectures with the reach, flexibility, and reusability of netcentric concepts. BENEFIT: VHACS presents a series of interesting initial commercialization opportunities that will be explored, and subsequently refined, over the course of this research.  The approaches taken in VHACS to automate hybrid execution through distributed discovery and composition and applying the results to solve complex problems have utility to a variety of commercial applications. The four most prominent include: 1) Logistics algorithms that focus on optimization can be combined with other algorithms to understand the propagating cascading effects that logistics contributes to, 2) Gaming algorithms and techniques developed for VHACS can be embedded into gaming engines (including military) to incorporate a more dynamic/realistic behavior based on composite algorithms. Especially with distributed gaming approaches, VHACS can dynamically alter the algorithms that comprise the executable hybrid architecture package to modify the behavior of virtual entities etc., 3) World Banking VHACS can invoke hybrid algorithms to understand how regional behaviors rapidly change based on perceptions of U.S. actions taken, VHACS could be used to understand regional stability issues that are of great concern to the world banking community, 4) Strategic Business Analysis there is a very close analogy between understanding an enemy, his likely courses of action and developing a plan to defeat him to that of understanding a business competitor, his likely aggressive business actions and developing a strategic business plan to dominate in a discrete business domain. It is clear that this research could significantly improve, or perhaps even supplant, current business analysis and planning techniques such as SWOT analysis.

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

113 SBIR/STTR records share this UEI (2002–2024). Reported award amounts total $64,663,050. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Health and Human Services

Agency intelligence

Department of Defense

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