The development of features in object concepts

Behavioral and Brain Sciences 21 (1):1-17 (1998)
  Copy   BIBTEX

Abstract

According to one productive and influential approach to cognition, categorization, object recognition, and higher level cognitive processes operate on a set of fixed features, which are the output of lower level perceptual processes. In many situations, however, it is the higher level cognitive process being executed that influences the lower level features that are created. Rather than viewing the repertoire of features as being fixed by low-level processes, we present a theory in which people create features to subserve the representation and categorization of objects. Two types of category learning should be distinguished. Fixed space category learning occurs when new categorizations are representable with the available feature set. Flexible space category learning occurs when new categorizations cannot be represented with the features available. Whether fixed or flexible, learning depends on the featural contrasts and similarities between the new category to be represented and the individual's existing concepts. Fixed feature approaches face one of two problems with tasks that call for new features: If the fixed features are fairly high level and directly useful for categorization, then they will not be flexible enough to represent all objects that might be relevant for a new task. If the fixed features are small, subsymbolic fragments (such as pixels), then regularities at the level of the functional features required to accomplish categorizations will not be captured by these primitives. We present evidence of flexible perceptual changes arising from category learning and theoretical arguments for the importance of this flexibility. We describe conditions that promote feature creation and argue against interpreting them in terms of fixed features. Finally, we discuss the implications of functional features for object categorization, conceptual development, chunking, constructive induction, and formal models of dimensionality reduction. Key Words: concept learning; conceptual development; features; perceptual learning; stimulus encoding.

Links

PhilArchive



    Upload a copy of this work     Papers currently archived: 91,102

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

Similar books and articles

New features for old: Creation or derivation?Cyril R. Latimer - 1998 - Behavioral and Brain Sciences 21 (1):31-32.
Do features arise out of nothing?Adriaan Tijsseling - 1998 - Behavioral and Brain Sciences 21 (1):38-39.
Who needs created features?Katja Wiemer-Hastings & Arthur C. Graesser - 1998 - Behavioral and Brain Sciences 21 (1):39-39.
Parts, features, and expertise.James Tanaka - 1998 - Behavioral and Brain Sciences 21 (1):37-38.

Analytics

Added to PP
2009-01-28

Downloads
70 (#217,681)

6 months
5 (#311,051)

Historical graph of downloads
How can I increase my downloads?

Citations of this work

Perceptual symbol systems.Lawrence W. Barsalou - 1999 - Behavioral and Brain Sciences 22 (4):577-660.
Rich or thin?Susanna Siegel & Alex Byrne - 2016 - In Bence Nanay (ed.), Current Controversies in Philosophy of Perception. New York: Routledge. pp. 59-80.
A Theory of Sentience.Austen Clark (ed.) - 2000 - New York: Oxford University Press.
Material symbols.Andy Clark - 2006 - Philosophical Psychology 19 (3):291-307.

View all 76 citations / Add more citations

References found in this work

Word and Object.Willard Van Orman Quine - 1960 - Cambridge, MA, USA: MIT Press.
Vision.David Marr - 1982 - W. H. Freeman.
Word and Object.Willard Van Orman Quine - 1960 - Les Etudes Philosophiques 17 (2):278-279.
The Language of Thought.J. A. Fodor - 1978 - Critica 10 (28):140-143.

View all 68 references / Add more references