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Abstract

While computational cognitive modelling within unified theories of cognition (UTC, Newell 1990) has made impressive strides throughout the last two decades, it still hosts little research on language. If language is what makes humans human, it is difficult to see how our cognitive models can come close to a comprehensive understanding of human cognition and intelligence without graceful inclusion of language.

In this short paper I make a first attempt to bridge the gap between computational linguistics and unified theories of cognition by finding a method to transfer research results from one to the other. In particular I describe a translation of repersentations in referential nets into the chunks of ACT-R's declarative memory representation.