An Ecological Model of Memory and Inferences

Daniela Link, Julian N. Marewski, Lael J. Schooler

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

3 Scopus citations

Abstract

In this paper, we develop a memory model that predicts retrieval characteristics of real-world facts. First, we show how ACT-R's memory model can be used to predict people's knowledge about real-world objects. The model assumes the probability of retrieving a chunk of information about an object and the time to retrieve this information depend on the pattern of prior environmental exposure to the object. Second, we use frequencies of information appearing on the Internet as a proxy for what information people would encounter in their natural environment, outside the laboratory. In two Experiments, we use this model to account for subjects' associative knowledge about real-world objects as well as the associated retrieval latencies. Third, in a computer simulation, we explore how such model predictions can be used to understand the workings and performance of decision strategies that operate on the contents of declarative memory.

Original languageEnglish (US)
Title of host publicationProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
EditorsAnna Papafragou, Daniel Grodner, Daniel Mirman, John C. Trueswell
PublisherThe Cognitive Science Society
Pages1883-1888
Number of pages6
ISBN (Electronic)9780991196739
StatePublished - 2016
Event38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016 - Philadelphia, United States
Duration: Aug 10 2016Aug 13 2016

Publication series

NameProceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016

Conference

Conference38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Country/TerritoryUnited States
CityPhiladelphia
Period8/10/168/13/16

Keywords

  • ACT-R
  • decision making
  • declarative memory
  • fast-and-frugal heuristics
  • Internet
  • strategy selection

ASJC Scopus subject areas

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

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