Abstract
The paper discusses a novel model for concept learning and representation. Two levels of representation are used: exemplars and (generalized concepts) prototypes. The internal structure of the model is based on a semantic network using spreading activation. Categorisation and addition operations are supported in parallel. Forgetting of learned concepts is used in order to track dynamic and novel environments. The model is inspired by the corresponding psychological theories of exemplars and prototypes. Simulation results support the formulation of the model. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Kasderidis, S. (2007). Developing concept representations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4669 LNCS, pp. 922–933). Springer Verlag. https://doi.org/10.1007/978-3-540-74695-9_94
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