Abstract
Modelling higher cognitive behaviour, namely symbol processing and rule in- ference, in the connectionist framework is inherently problematic, especially if one strives for biological realism. Problems like compositionality and variable binding, as well as the selection of a suitable representation scheme, are a ma- jor obstacle to achieving the kind of intelligent behaviour which would extend beyond simple pattern recognition. Although there are connectionist systems which are capable of advanced inferencing (cf. Shastri and Ajjanagadde [8], or Barnden [3]), they always compromise their exibility and, most importantly, their capability to learn. All connections in such systems are fixed, having been carefully prearranged by the designer.
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Chady, M. (2001). Modelling Higher Cognitive Functions with Hebbian Cell Assemblies. In: Wermter, S., Austin, J., Willshaw, D. (eds) Emergent Neural Computational Architectures Based on Neuroscience. Lecture Notes in Computer Science(), vol 2036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44597-8_29
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DOI: https://doi.org/10.1007/3-540-44597-8_29
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