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Mental and Qualitative (AI) Models of Cardiac Electrophysiology: An Exploratory Study in Comparative Cognitive Science

  • K. J. Gilhooly
  • P. McGeorge
  • J. Hunter
  • J. M. Rawles
  • I. K. Kirby
Conference paper
Part of the NATO ASI Series book series (volume 97)

Abstract

A key tenet in cognitive science is that intelligent systems require internal models of external phenomenon for purposes of prediction and control. In cognitive psychology the general notion of “mental models” is well established, although there is no universal agreement on how mental models can be characterised in detail (Gentner & Stevens 1983; Holland et al. 1986; Gilhooly 1987). In artificial intelligence (AI) the area of “qualitative modelling” is undergoing intensive investigation in a range of domains from naive physics to medical diagnosis (e.g., Kuipers 1986; Hunter et al. 1991). Qualitative models may be seen as complementary to the more established quantitative forms of computer modelling. Although qualitative models are less precise, they would seem much closer to human forms of thinking. Since mental models themselves are most plausibly assumed to be qualitative in character, there is a striking convergence of interest in qualitative modelling processes from the viewpoints of cognitive psychology and AI.

Keywords

Recognition Accuracy Causal Explanation Qualitative Model Distractor Item Cardiac Electrophysiology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • K. J. Gilhooly
    • 1
  • P. McGeorge
    • 1
  • J. Hunter
    • 2
  • J. M. Rawles
    • 3
  • I. K. Kirby
    • 2
  1. 1.Psychology DepartmentAberdeen UniversityAberdeenScotland, UK
  2. 2.Computing Science DepartmentAberdeen UniversityUK
  3. 3.Medicine and Therapeutics DepartmentAberdeen UniversityUK

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