A preference for the unpredictable over the informative during self-directed learning

Doug Markant, Todd M. Gureckis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The potential information gained from asking a question and one's uncertainty about the answer to that question are not always the same. For example, given a coin that one believes to be fair, the uncertainty a person has about the outcome of flipping that coin is high, but either outcome is unlikely to make them believe that the coin is biased (i.e., the “information gain” of that observation is low). In the present paper we show that people use a simple form of predictive uncertainty to guide their information sampling decisions, a strategy which is often equivalent to maximizing information gain, but is less efficient in environments where potential queries vary in their reliability. We conclude that a potentially powerful driver of human information gathering may be the inability to predict what will happen as a result of an action or query.

Original languageEnglish (US)
Title of host publicationProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PublisherThe Cognitive Science Society
Pages958-963
Number of pages6
ISBN (Electronic)9780991196708
StatePublished - 2014
Event36th Annual Meeting of the Cognitive Science Society, CogSci 2014 - Quebec City, Canada
Duration: Jul 23 2014Jul 26 2014

Publication series

NameProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

Conference

Conference36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Country/TerritoryCanada
CityQuebec City
Period7/23/147/26/14

Keywords

  • active learning
  • information search
  • self-directed learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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