Research Group Cognitive and Engineering Psychology
Research Group Cognitive and Engineering Psychology

Fuzzy Logic

fuzzyReal-world diagnostic reasoners, such as physicians, are almost always confronted with different kinds of uncertainty, for instance probabilistic relations, imprecision or ambiguity of information. Our intention is to investigate the influence of uncertainty in the context of diagnostic reasoning processes. Current research focusses on precise (numerical) or vague (verbal) probabilistic links between causes and effects and their influence on diagnostic performance, plausibility ratings and probability estimations of hypotheses during the reasoning process. Predictions of normative models (e.g. Bayes nets) are compared with the empirical results and analysis methods especially suitable for dealing with uncertainty (e.g. fuzzy pattern classification) are applied (e.g. Baumann, Bocklisch, Jahn, Mehlhorn, & Krems, 2008).

References

  • Baumann, M., Bocklisch, F., Jahn, G., Mehlhorn, K. & Krems, J.F. (2008). How people cope with uncertainty and complexity in diagnostic reasoning tasks. In C. Dalbert (Hrsg.), XXIX International Congress of Psychology: Abstracts: A Special Issue of the International Journal of Psychology. Hove: Psychology Press.

  • Bocklisch, F. (2011). The Vagueness of verbal probability and frequency expressions. International Journal of Advanced Computer Science, 1(2) , 52-57.

  • Bocklisch, F., Bocklisch, S.F., & Krems, J.F. (2010a). How to Translate Words into Numbers? A Fuzzy Approach for the Numerical Translation of Verbal Probabilities. In Hüllermeier, E., Kruse, R. und Hoffmann, F. (Hrsg.), IMPU 2010, LNAI 6178, (pp. 614-623). Heidelberg - Berlin: Springer.

  • Bocklisch, F., Bocklisch, S. F., & Krems, J.F. (2012). Sometimes, often, and always: Exploring the vague meanings of frequency expressions. Behaviour Research Methods, 44(1), 144-157. doi: 10.3758/s13428-011-0130-8

 

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