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Integrated Cognitive Architectures For Robust Decision Making
Final technical rept. 1 Jul 2008-30 Nov 2009
CARNEGIE-MELLON UNIV PITTSBURGH PA
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Introduction The project s goal was to reproduce robust and intelligent decision making capabilities in artificial agents by integrating two successful cognitive architectures, ACT-R Anderson, 2007 and Leabra O Reiily Munakata, 2000. The rationale was that such an integration effort would yield insights on the general mechanisms that allow rapid decision-making in real-time. Taken separately, ACTR and Leabra incorporate different views of how decision-making and robust behavior occur. The two architectures have different and complementary strengths and weaknesses and work at different levels of abstractions. Thus, an integration of the two would possibly yield a uniform framework for understanding the computational basis of robust intelligence and decision-making in humans.
APPROVED FOR PUBLIC RELEASE