Kurup, Unmesh
Reports of the AAAI 2009 Fall Symposia
Azevedo, Roger (University of Memphis) | Bench-Capon, Trevor (University of Liverpool) | Biswas, Gautam (Vanderbilt University) | Carmichael, Ted (University of North Carolina at Charlotte) | Green, Nancy (University of North Carolina at Greensboro) | Hadzikadic, Mirsad (University of North Carolina at Charlotte) | Koyejo, Oluwasanmi (University of Texas) | Kurup, Unmesh (Rensselaer Polytechnic Institute) | Parsons, Simon (Brooklyn College, City University of New York) | Pirrone, Roberto (University of Pirrone) | Prakken, Henry (Utrecht University) | Samsonovich, Alexei (George Mason University) | Scott, Donia (Open University) | Souvenir, Richard (University of North Carolina at Charlotte)
Series, held Thursday through Saturday, November 5-7, at he Association for the Advancement of Artificial Intelligence the Westin Arlington Gateway in Arlington, Virginia. The titles of the seven symposia were as follows: (1) Biologically Inspired Cognitive Biologically Inspired Cognitive Architectures Architectures, (2) Cognitive and Metacognitive Cognitive and Metacognitive Educational Systems Educational Systems, (3) Complex Adaptive Complex Adaptive Systems and the Threshold Effect: Views from the Natural Systems and the Threshold Effect: Views and Social Sciences from the Natural and Social Sciences, (4) Manifold Manifold Learning and Its Applications Learning and Its Applications, (5) Multirepresentational Architectures for Human-Level Multirepresentational Architectures for Human-Level Intelligence Intelligence, (6) The Uses of Computational The Uses of Computational Argumentation Argumentation, and (7) Virtual Healthcare Virtual Healthcare Interaction Interaction. An informal reception was held on Thursday, November 5. A general plenary session, in which the highlights of each symposium were presented, was held on Friday, November 6. The challenge of creating a real-life computational equivalent of the human mind requires that we better understand at a computational level how natural intelligent systems develop their cognitive and learning functions. They will behave, variety of disjoined communities and schools of learn, communicate, and "think" as conscious thought that used to speak different languages and beings in general, in addition to being able to perform ignore each other.
Multi-modal Systems As Multi-representational Systems
Kurup, Unmesh (Rensselaer Polytechnic Institute) | Chandrasekaran, B (The Ohio State University)
In earlier work, we have shown how a cognitive architecture can be augmented with a diagrammatic reasoning system to produce a bimodal cognitive architecture. In this paper, we show how this bimodal architecture is also bi-representational (multi-representational in the general case) by describing a desiderata for representational formalisms and showing how the diagrammatic representation in biSoar satisfies these requirements.