Within cognitive science, two approaches currently dominate the
problem of modeling representations. The symbolic approach views
cognition as computation involving symbolic manipulation.
Connectionism, a special case of associationism, models
associations using artificial neuron networks. Peter Gardenfors
offers his theory of conceptual representations as a bridge between
the symbolic and connectionist approaches.
Symbolic representation is particularly weak at modeling concept
learning, which is paramount for understanding many cognitive
phenomena. Concept learning is closely tied to the notion of
similarity, which is also poorly served by the symbolic approach.
Gardenfors's theory of conceptual spaces presents a framework for
representing information on the conceptual level. A conceptual
space is built up from geometrical structures based on a number of
quality dimensions. The main applications of the theory are on the
constructive side of cognitive science: as a constructive model the
theory can be applied to the development of artificial systems
capable of solving cognitive tasks. Gardenfors also shows how
conceptual spaces can serve as an explanatory framework for a
number of empirical theories, in particular those concerning
concept formation, induction, and semantics. His aim is to present
a coherent research program that can be used as a basis for more
detailed investigations."
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