Grounding the Unobservable in the Observable: The Role and Representation of Hidden State in Concept Formation and Refinement

Abstract

One of the great mysteries of human cognition is how we learn to discover meaningful and useful categories and concepts about the world. Why do very young children acquire concepts like "animate" rather than "blue with red and green dots"? One answer to this question is that categories are created, refined and maintained to support accurate prediction. Knowing that an entity is animate is generally more useful for the purpose of predicting how it will behave than knowing that it is blue with red and green dots. The idea of using predictability, or a lack thereof, as the driving force behind the creation and refinement of knowledge structures has been applied in a variety of context. Virtually all of the work in this vein is based on two key assumptions. First, an assumption is made that the world is in principle deterministic; that given enough knowledge, outcomes can be predicted. Given this, an agent's failure to predict implies that it is either missing information or incorrectly representing information. Second, it is assumed that knowledge structures sufficient for the task can be created by combining raw perceptual information in various ways. That is, everything the agent needs to make accurate predictions is available in its percepts, and the problem facing the agent is to find the right combination of elements. Our position is that the first of these assumptions represents a useful mechanism for driving unsupervised concept acquisition, whereas blind adherence to the second makes it difficult or impossible to discover some of the most fundamental concepts. To explain observed phenomena, scientists often posit the existence of unobservable entities. No one has ever seen gravity or black holes, but they explain a wide range of observable phenomena. Scientific progress would come to a standstill if not for the ability to posit and collect evidence for the existence of causally efficacious entities that do not manifest themselves directly in our percepts.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2001
Accession Number
ADA462269

Entities

People

  • Clayton T. Morrison
  • Gary King
  • Tim Oates

Organizations

  • University of Massachusetts Amherst

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Acquisition
  • Artificial Intelligence
  • Black Holes
  • Cognition
  • Computer Science
  • Computers
  • Concept Formation
  • Environment
  • Feedback
  • Haptics
  • Information Operations
  • Language
  • Learning
  • Massachusetts
  • Mental Processes
  • Observation

Readers

  • Educational Psychology
  • Neural Network Machine Learning.
  • Systems Analysis and Design