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Cross-Domain Modeling of Human Cognition (SS 2019)

Organizer: Marco Ragni
Assistants: Nicolas Riesterer, Daniel Brand


Traditionally, cognitive science aimed at connecting experimental psychological research with computational modelling techniques typical for computer science and artificial intelligence (AI). In this seminar, we make an attempt at tying both research fields even closer together. By defining a prediction setting, the goal is to develop modern models capable of forecasting human responses to reasoning tasks based on concepts inspired by machine learning and AI. In particular, seminar participants will be given the chance to extend existing approaches or develop new accounts on their own.

The models will deal with the domain of conditional and syllogistic reasoning.

Theoretical Background

  • Khemlani, S., & Johnson-Laird, P. N. (2012). Theories of the syllogism: A meta-analysis. Psychological bulletin138(3), 427.
  • Hattori, M. (2016). Probabilistic representation in syllogistic reasoning: A theory to integrate mental models and heuristics. Cognition157, 296-320.
  • da Costa, A. O., Saldanha, E. A. D., Hölldobler, S., & Ragni, M. (2017). A computational logic approach to human syllogistic reasoning. In Proceedings of the 39th Annual Conference of the Cognitive Science Society.
  • Riesterer N., Brand D., Ragni M. (2018). The Predictive Power of Heuristic Portfolios in Human Syllogistic Reasoning. In: Trollmann F., Turhan AY. (Eds.) KI 2018: Advances in Artificial Intelligence. KI 2018. Lecture Notes in Computer Science, vol 11117. Springer, Cham.
  • Singmann, H., Klauer, K. C., & Beller, S. (2016). Probabilistic conditional reasoning: Disentangling form and content with the dual-source model. Cognitive Psychology88, 61-87.

Important Dates & Deadlines

  • April 25th, 13:00-14:00, building 52, room 02-017: Introductory Meeting
  • April 23th - May 1st: Registration HisInOne
  • May 29th, 12:00-14:00, building 51, room 00-034: Midterm presentation of preliminary results
  • July 7th, 23:59: Deadline for final models & written report
  • July 12th-13th, 9:00-18:00, building 82 (Mensa), room 00-006 (Kinohörsaal): Blockseminary


  • Conceptualization, analysis and implementation of a model for syllogistic reasoning in the CCOBRA framework
  • Presentation of your preliminary & final results
    • Theoretical and computational foundation
    • Predictive performance
    • Ideas for improvement
  • Written report of your work (~6 pages, CogSci Layout)
    • Introduction/Motivation
    • Theoretical Foundation
    • Method/Model
    • Results
    • Conclusions/Discussion