UBER-HEB: Universal Biologically-inspired Environment for Research: Hierarchical Ersatz Brain

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: W31P4Q-08-C-0433
Agency Tracking Number: 08ST1-0122
Amount: $99,000.00
Phase: Phase I
Program: STTR
Awards Year: 2008
Solicitation Year: 2008
Solicitation Topic Code: ST081-006
Solicitation Number: 2008.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
 Paul Allopenna
 Senior Cognitive Scientist
 (781) 496-2486
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Email: clancy@aptima.com
Research Institution
 Michael Gaughan
 Box 1929
164 Angell Street, 3rd Floor
Providence, RI, 2912
 (401) 863-1799
 Nonprofit college or university
Decades of exponential advancement in computer capabilities have transformed the world, from toddlers’ playthings to the technologies of war and peace. Some further advances are constrained by the limits of von Neumann machines; in particular, they do not learn well. Aptima proposes to conduct a feasibility study to design “UBER-HEB,” a non-von Neumann hierarchical universal learning system. The work is grounded in the Ersatz Brain Project, a biologically-inspired architecture for cognitive computing, based on decades of research by Professor James Anderson of Brown University, a founder of neural networks. The team members have collaborated for a decade. The approach uses many sparsely connected modules inspired by cortical columns. Learning takes places via several integrated mechanisms: Hebbian, dynamic systems forming attractors, interference patterns of activations. It includes hierarchical structures and hierarchical properties also emerge naturally. It takes a biologically plausible and computationally powerful topographical approach to temporal encoding. We will structure the work around three test problems, for which we will develop running code. One of the problems concerns anomaly detection, which is of clear operational relevance. The feasibility assessment and resulting design will thus be based on both theoretical considerations and the results and analysis of the test problems.

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

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