Modeling cognitive development on the balance scale task

  • Authors:
  • Stephanie Sage;Pat Langley

  • Affiliations:
  • The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania;The Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania

  • Venue:
  • IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 1983

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Abstract

In this paper we describe a production system model of children's development on the balance scale task. Starting with a set of rules that makes random predictions, the system iearns from its errors and improves as it gains experience. The transition mechanism is a discrimination process that searches for differences between cases in which correct predictions are made and cases in which errors are made The stages through which the system progresses are very similar to those observed in children, so the model provides an explanation of the observed developmental trends Since the system has no notion of torque, it never acquires the ability to completely predict the balance scale's behavior; however, it is able to learn heuristically useful rules despite its incomplete representation of the environment, much as children do.