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Software Workspace for creating and testing Algorithmic Responses based on Meta-heuristic Experimental Designs (SWARMED)

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-17-C-0034
Agency Tracking Number: D162-005-0096
Amount: $99,992.08
Phase: Phase I
Program: SBIR
Solicitation Topic Code: SB162-005
Solicitation Number: 2016.2
Solicitation Year: 2016
Award Year: 2017
Award Start Date (Proposal Award Date): 2017-01-26
Award End Date (Contract End Date): 2017-10-26
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. Corey Lofdahl
 Senior Scientist
 (617) 491-3474
Business Contact
 Mark Felix
Phone: (617) 491-3474
Research Institution

Military operators are challenged by managing, gaining information from, and reacting to autonomous systems. Additional challenges arise from providing autonomous systems with the means to maintain resilience, be adaptable, and help military operators understand the control strategies employed by autonomous systems, whether those strategies are intentional or arise from emergent interactions. These challenges lend themselves to meta-heuristic control strategies because it is difficult to determine a priori which strategies will perform well and system architects have insufficient heuristic information to leverage for their designs. To address these system design issues, we propose a Software Workspace for creating and testing Algorithmic Responses based on Meta-heuristic Experimental design (SWARMED). By designing and pilot testing operationally-inspired, biosystem-based experiments and collecting data from live test populations, our workspace will translate analyzed experimental data into system dynamics and agent based models to develop our algorithms. Additionally, SWARMED will include a software-based, bio-inspired algorithm validation workspace to test, analyze, and demonstrate the new bio-inspired algorithms.

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

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