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Related Experiment Videos

Domain-creating constraints.

Robert L Goldstone1, David Landy

  • 1Department of Psychological and Brain Sciences, Indiana University Department of Psychology, University of Richmond.

Cognitive Science
|May 14, 2011
PubMed
Summary
This summary is machine-generated.

Learning involves developing constraints that shape future learning, with some constraints being learnable themselves. This research explores how cognitive development can establish domains from rich inputs, rather than relying on pre-existing ones.

Related Experiment Videos

Area of Science:

  • Cognitive Science
  • Developmental Psychology
  • Machine Learning

Background:

  • Learning efficiency often relies on pre-defined constraints.
  • Previous models assumed domain-specific constraints were innate.
  • The role of learnable constraints in cognitive development is an emerging area.

Purpose of the Study:

  • To explore how learning involves developing and utilizing constraints.
  • To investigate the possibility of learning domains themselves.
  • To propose models of cognitive development that exhibit genuine novelty.

Main Methods:

  • Analysis of contributions to a special issue on cognitive development.
  • Examination of how general cognitive constraints interact with rich inputs.
  • Utilizing two physical, mechanistic models for tone discrimination learning.

Main Results:

  • Learning systems can develop constraints that guide subsequent learning.
  • Domains can be established through general cognitive constraints and rich input, not necessarily pre-existing.
  • Mechanistic models preserving rich perceptual information can form novel hypotheses and encodings.

Conclusions:

  • Cognitive development can be characterized by the emergence of learnable constraints and domains.
  • Models of development should move beyond symbolic encodings to allow for greater flexibility and novelty.
  • Rich, concrete information processing is key to forming new cognitive structures.