Cognitive Models for learning to control dynamic systems

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9550-08-C-0044
Agency Tracking Number: F074-012-0118
Amount: $100,000.00
Phase: Phase I
Program: STTR
Awards Year: 2008
Solicitation Year: 2007
Solicitation Topic Code: AF07-T012
Solicitation Number: N/A
Small Business Information
1953, 68th Street, Brooklyn, NY, 11204
DUNS: 190577200
HUBZone Owned: N
Woman Owned: Y
Socially and Economically Disadvantaged: N
Principal Investigator
 Zhong-Ping Jiang
 Chief Scientist
 (718) 260-3646
Business Contact
 Xiaoming Zhuang
Title: President
Phone: (917) 767-8142
Research Institution
 Zhong-Ping Jiang
 Six Metrotech Center
Brooklyn, NY, 11201
 (718) 260-3646
 Nonprofit college or university
The development of fast and robust learning models which can work in non-stationary environments or scenarios with rapidly changing goals is becoming a critical task in both military and civilian applications. The objective of this proposal is to develop new mathematical/computational models based on cognitive science principles that are capable of rapid learning for command and control problems. In Phase I, the focus is on the integration of current cognitive models, such as DFT, with practical methods in nonlinear systems and control theory. Stochastic resonance techniques will be applied for the first time to dynamic signal detection and dynamic decision-making tasks. The efficiency of the proposed cognitive learning algorithms will be tested and evaluated based on previously established experimental research with human decision tasks. Phase II will focus on the development of software for application of these novel learning models to some Air Force missions of critical importance. This phase involves both computer simulations and experimental validations with human decision tasks.

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

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