Integrated Cognitive Architectures For Robust Decision Making
Abstract
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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 20, 2010
- Accession Number
- ADA561318
Entities
People
- Andrea Stocco
- Christian Lebiere
- John R. Anderson
- Randall C. O'Reilly
Organizations
- Carnegie Mellon University