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Proceedings Paper

Proactive learning for artificial cognitive systems
Author(s): Soo-Young Lee
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Paper Abstract

The Artificial Cognitive Systems (ACS) will be developed for human-like functions such as vision, auditory, inference, and behavior. Especially, computational models and artificial HW/SW systems will be devised for Proactive Learning (PL) and Self-Identity (SI). The PL model provides bilateral interactions between robot and unknown environment (people, other robots, cyberspace). For the situation awareness in unknown environment it is required to receive audiovisual signals and to accumulate knowledge. If the knowledge is not enough, the PL should improve by itself though internet and others. For human-oriented decision making it is also required for the robot to have self-identify and emotion. Finally, the developed models and system will be mounted on a robot for the human-robot co-existing society. The developed ACS will be tested against the new Turing Test for the situation awareness. The Test problems will consist of several video clips, and the performance of the ACSs will be compared against those of human with several levels of cognitive ability.

Paper Details

Date Published: 13 April 2010
PDF: 6 pages
Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 770309 (13 April 2010); doi: 10.1117/12.855044
Show Author Affiliations
Soo-Young Lee, Korea Advanced Institute of Science and Technology (Korea, Republic of)


Published in SPIE Proceedings Vol. 7703:
Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII
Harold H. Szu; F. Jack Agee, Editor(s)

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