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Cross-Domain Strategic Planning with Adaptation for Risk Uncertainty and Opportunistic Targeting

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8750-22-C-1006
Agency Tracking Number: F21B-T001-0010
Amount: $156,388.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF21B-T001
Solicitation Number: 21.B
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-01-11
Award End Date (Contract End Date): 2022-06-11
Small Business Information
300 W MAIN ST STE 301
United States
DUNS: 028211527
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Fowler
 (540) 266-0671
Business Contact
 William Goodrum
Phone: (434) 227-5884
Research Institution
 Virginia Tech Hume Center for National Security and Technology
 Aaron Akers
1311 Research Center Drive
Blacksburg, VA 24061-0001
United States

 (540) 231-1967
 Nonprofit College or University

Elder Research, Inc. (ERI) and the Virginia Tech Hume Center bring together a data science team with operational context in advanced AI/ML workflow development and implementation, and successful research in semantic reasoning, planning under uncertainty, and hierarchical multi-agent tactical planning. Through applying autonomy to tactical planning and execution, we have come to understand the importance of developing models and plans that are inherently flexible, and allow adaptation to the changing battlefield environment. Our proposed approach for operational and strategic planning is based on an agnostic concurrent, hierarchical graph search planning algorithm that accounts for the curse of dimensionality, environmental and adversarial uncertainty, cross-domain optimization, domain-specific optimization algorithms, and the risk inherent in tactical execution. The key innovation of this algorithm is its ability to generate multiple courses of action across domains and hierarchies that inherently account for risk in the battlespace environment, reducing the planning cycle and enabling opportunistic targeting based on C4ISR.

* Information listed above is at the time of submission. *

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