Ecological Resources for Modeling Interactive Behavior and Embedded Cognition

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A recent trend in cognitive modeling is to couple cognitive architecture with computer models or simulations of dynamic environments to study interactive behavior and embedded cognition. Progress in this area is made difficult because cognitive architectures traditionally have been motivated by data from discrete experimental trials using static, non-interactive tasks. As a result, additional theoretical problems must be addressed to bring cognitive architectures to bear on the study of cognition in dynamic and interactive environments. This chapter explore three such problems dealing with the need to model the sensitivity of behavior to environmental constraints, the need to model highly context-specific adaptations underlying expertise, and the need for environmental modeling at a functional level. It illustrates these problems and describes how they have been addressed in a study on modeling interactive behavior and embedded cognition.

Original languageEnglish (US)
Title of host publicationIntegrated Models of Cognitive Systems
PublisherOxford University Press
ISBN (Electronic)9780199847457
ISBN (Print)9780195189193
DOIs
StatePublished - Mar 22 2012

Fingerprint

Cognition
Computer Simulation

Keywords

  • Adaptations
  • Cognitive architecture
  • Cognitive modeling
  • Dynamic environments
  • Embedded cognition
  • Environmental constraints
  • Environmental modeling
  • Expertise
  • Interactive behavior

ASJC Scopus subject areas

  • Psychology(all)

Cite this

Ecological Resources for Modeling Interactive Behavior and Embedded Cognition. / Kirlik, Alex.

Integrated Models of Cognitive Systems. Oxford University Press, 2012.

Research output: Chapter in Book/Report/Conference proceedingChapter

Kirlik, Alex. / Ecological Resources for Modeling Interactive Behavior and Embedded Cognition. Integrated Models of Cognitive Systems. Oxford University Press, 2012.
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