Mixed Initiative Machine for Instructed Computing: MIMIC II

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-08-C-0738
Agency Tracking Number: N074-031-0199
Amount: $500,000.00
Phase: Phase II
Program: STTR
Awards Year: 2008
Solicitation Year: 2007
Solicitation Topic Code: N07-T031
Solicitation Number: N/A
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, 01801
DUNS: 967259946
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Yuri Levchuk
 Senior Scientist and Engineer
 (202) 552-6136
 levchuk@aptima.com
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Email: clancy@aptima.com
Research Institution
 COGNITIVE ENGINEERING RESEARCH INST
 Steven M Shope
 5865 South Sossaman Road
Mesa, AZ, 85212
 (408) 988-1000
 Domestic nonprofit research organization
Abstract
In less than a decade, UAVs have transitioned from a curiosity on the battlefield to a core capability for intelligence and attack. However, the intelligence that drives tactical decision making and flight control remains firmly lodged in the heads of expert operators. As more UAVs and other unmanned vehicles enter the battlespace, intelligent, autonomous UAVs will become a necessity. To address this challenge, Aptima, Boeing, and the Cognitive Engineering Research Institute propose to (1) conduct human subjects experiments that illuminate the potential for humans to convey their knowledge of autonomous tactical decision making and control to UAVs, and to (2) prototype training support technology and machine learning algorithms that enable UAVs to learn from expert UAV operators. We call the proposed capability MIMIC: Mixed Initiative Machine for Instructed Computing. MIMIC is a hybrid model that integrates psychological learning theory and rapid machine learning algorithms to enable human operator to teach the UAV new tactical and control behaviors through a unique user interface to a UAV mission simulator. MIMIC will enable UAVs to infer the mission threats and opportunities and to dynamically optimize tactical decisions and control actions when the user cannot do so or obligates the UAV to do so.

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

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