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Modeling and Simulation for Design, Development, Testing and Evaluation of Autonomous Multi-Agent Models

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-16-C-6725
Agency Tracking Number: F15A-T14-0134
Amount: $749,963.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: AF15-AT14
Solicitation Number: 2015.0
Solicitation Year: 2015
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-08-16
Award End Date (Contract End Date): 2018-11-15
Small Business Information
136 SW Washington Ste 203
Corvallis, OR 97333
United States
DUNS: 111494303
HUBZone Owned: Yes
Woman Owned: Yes
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Benjamin Bell, Ph.D.
 (541) 753-0844
Business Contact
 Andrew Arnold
Phone: (541) 753-0844
Research Institution
 Florida Institute for Human and Machine Cognition
 Sharon Heise, Ph.D.
40 S. Alcaniz St. Array
Pensacola, FL 32502
United States

 (850) 202-4465
 Nonprofit College or University

U.S. forces are benefiting from automation systems of unprecedented sophistication, empowered by advances in artificial intelligence (AI) and human-systems interaction. In air combat operations, onboard intelligent assistants monitor the aircraft, interpret and carry out commands, and report aircraft and system status, mission progress, threats and alerts. Because pilots and agents are part of a network that may involve ambiguous communications and dynamic roles and responsibilities, Anti-Access/Area Denial (A2AD) raises significant implications for how aircrew can work with their intelligent associates. There is thus a need for training, concepts of operations (CONOPS), and tactics, techniques, and procedures (TTPs) to combat this threat. A2AD effects can have devastating effects on how people and intelligent systems work together. An urgent need has surfaced for a robust capability to simulate, test, predict, and evaluate how these human/agent teams can succeed when faced by both nominal and adverse conditions. In Phase I, we demonstrated a framework that overcomes limitations of current modeling approaches, which are not adequate to properly capture work practices of the socio-technical system. In Phase II, we propose creating a contested airspace simulation testbed that addresses this urgent need using an innovative application of a sophisticated and proven work practice analysis simulation.

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

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