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New approaches to cognition: Developing and testing a multifaceted view on similarity
Third-party funded project
Project title New approaches to cognition: Developing and testing a multifaceted view on similarity
Principal Investigator(s) Seitz, Florian
Co-Investigator(s) Rieskamp, Jörg
von Helversen, Bettina
Jarecki, Jana
Organisation / Research unit Departement Psychologie / Economic Psychology (Rieskamp)
Department Departement Psychologie / Economic Psychology (Rieskamp)
Project start 01.09.2020
Probable end 31.08.2024
Status Active
Abstract

Current state of research and project motivation. Similarity lies at the heart of many higher-order cognitive processes such as categorization and judgments. To date, however, the mechanisms by which people represent similarity in judgment and decision making are not well understood. Past research has traditionally followed the Euclidean view on similarity, assuming that the similarity of objects is a function of their differences on the features which constitute the objects. However, the Euclidean similarity has several limitations, including that it treats features separately and is insensitive to correlations among features, whereas people can be sensitive to correlated features. Therefore, further research is needed to uncover how people represent similarity.

Main research question and aim. I argue for a multifaceted view on similarity, which emphasizes that the psychology of similarity comprises multiple useful cognitive similarity mechanisms beyond the Euclidean similarity. My thesis will develop the multifaceted view in four connected theoretical and empirical lines of work, aiming at understanding the processes of psychological similarity representation in higher-order cognition.

Projects. Project 1 reviews the success and limitations of the Euclidean similarity in cognitive psychology and how machine learning can enrich current psychological theories. In the remaining three projects, I empirically test new hypotheses derived from the multifaceted view on similarity. Project 2 tests how people adapt the way they represent similarity to the current situation. Project 3 tests if an alternative similarity representation can explain a prominent judgmental bias, the conjunction fallacy. Project 4 tests how people represent similarity in real image classification by combining machine learning and cognitive modeling on big data.

Method, expected results, and impact. I use an open-science, open-data, open-code approach. I combine experimental data with inferential Bayesian statistics and computational cognitive modeling, relying on my modeling expertise from my Master’s thesis. My thesis will shed light on human learning, adaptation, and representation of similarity and impact the theories in cognitive and decision sciences and general psychology that are based on psychological similarity. The Ph.D. will result in four publications in international peer-reviewed outlets in the fields of cognitive and decision sciences, general psychology, and machine learning.

Keywords cognition, cognitive modeling, psychology
Financed by Swiss National Science Foundation (SNSF)
   

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23/05/2024