Proceedings:
Between a Rock and a Hard Place: Cognitive Science Principles Meet AI-Hard Problems
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Papers from the 2006 AAAI Spring Symposium
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Abstract:
Integrating social statics and dynamics into a single mathematical theory is one of the hard problems that could cross-fertilize AI and cognitive science. How perception, language and action are situated by context and grounded in reality remains one of the grand challenges of AI and cognitive science (see the special issue of Artificial Intelligence, 2005, 167). There are claims that it has been partly solved in AI from a programming perspective (i.e., the frame problem), but no similar claim exists in contemporary cognitive science, although Kurt Lewin began the study of it more than 70 years ago. The central problem remains the lack of a mathematical theory of information interdependence generated by social situations as when forming a dyad between two agents alters the cognitions of both. But the quantum mathematical model of social interdependence has recently gained credibility in the field and from a pilot study in the laboratory that we are attempting to replicate with AI.
Spring
Papers from the 2006 AAAI Spring Symposium