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Projekt Druckansicht

Das 2N-ary Choice Tree (2NCT) Modell für Entscheidungen zwischen mehreren Alternativen mit mehreren Attributen: Weiterentwicklung und empirische Tests.

Fachliche Zuordnung Allgemeine, Kognitive und Mathematische Psychologie
Förderung Förderung von 2015 bis 2021
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 281130457
 
Erstellungsjahr 2021

Zusammenfassung der Projektergebnisse

Two leading computational models for multi-alternative decision problems – multi-alternative Decision Field Theory (MDFT) and the Leaky Competing Accumulator (LCA) model – primarily focus on accounting simultaneously for three context effects: similarity, compromise and attraction. These effects may occur when a third alternative is added to a choice set of two. Both models can be interpreted as a neural network with four layers. Predictions of these models have only been derived via simulations. The project proposes an alternative approach, which includes some of the assumptions made previously and tries to overcome some of the computational problems these models have. The main goal of the present proposal is fourfold. For the theoretical part, it seeks to (1) further develop and explore an alternative decision model for multiple choice options (2N-ary Choice Tree, 2NCT), with multiple attributes based on a tree structure rather than on neural nets; (2) provide an analytical solution for choice probabilities and choice response times rather than relying on simulations only and, in addition, provide algorithms allowing for efficient model fitting procedures. For the empirical part, the proposal seeks to (3) develop a new device for conducting choice experiments with multiple alternatives and attributes and, therewith, (4) design experiments that test the model in ways that go beyond producing merely the three context effects.

Projektbezogene Publikationen (Auswahl)

  • (2017). A Computational Model for Constructing Preferences for Multiple Choice Options. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. J. Davelaar (Eds.), Proceedings of the 39th annual conference of the cognitive science society (pp. 1351–1356). Austin, TX: Cognitive Science Society
    Wollschläger, L.M., & Diederich, A.
  • (2019). A computational cognitive process model for multi-alternative multi-attribute preferential choice. PhD thesis, Jacobs University Bremen
    Wollschläger, L.M.
  • (2020). Similarity, attraction, and compromise effects: Original findings, recent empirical observations, and computational cognitive process models. American Journal of Psychology, 133,1,1–30
    Wollschläger, L.M., & Diederich, A.
    (Siehe online unter https://doi.org/10.5406/amerjpsyc.133.1.0001)
  • Decision with multiple alternatives: geometric models in higher dimensions – the disk model. Journal of Mathematical Psychology
    Mallahi-Karai, K. & Diederich, A.
    (Siehe online unter https://doi.org/10.1016/j.jmp.2020.102493)
 
 

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