Generalisation: mechanistic and functional explanations |
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Authors: | Ken Cheng |
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Institution: | (1) Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia, |
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Abstract: | An overview of mechanistic and functional accounts of stimulus generalisation is given. Mechanistic accounts rely on the
process of spreading activation across units representing stimuli. Different models implement the spread in different ways,
ranging from diffusion to connectionist networks. A functional account proposed by Shepard analyses the probabilistic structure
of the world for invariants. A universal law based on one such invariant claims that under a suitable scaling of the stimulus
dimension, generalisation gradients should be approximately exponential in shape. Data from both vertebrates and invertebrates
so far uphold Shepard's law. Some data on spatial generalisation in honeybees are presented to illustrate how Shepard's law
can be used to determine the metric for combining discrepancies in different stimulus dimensions. The phenomenon of peak shift
is discussed. Comments on mechanistic and functional approaches to generalisation are given.
Accepted after revision: 10 September 2001
Electronic Publication |
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Keywords: | Generalisation Mechanism Function Honeybees Landmark |
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