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Cognitive Modeling (SS 2021)

Conditional Reasoning and Cognitive Models

Organizer: Marco Ragni
Assisstants: Daniel Brand, Hannah Dames, Sara Todorovikj

Conditionals are statements describing a causal relationship between two propositions. Given the current state of one of them (also called a minor premise), a conclusion about the other one can be deduced. Consider the following example:


If he has measles, then he has a fever.  (Conditional)

He has measles. (Minor Premise)

 

Given this information, you can now make a conclusion what, if anything, follows. Almost all people would infer that "he has a fever". This inference form is called Modus Ponens and is one of four forms that conditional reasoning research focuses on.

Over the years, a vast amount of cognitive theories for conditional reasoning have been proposed on different bases: formal logic, mental models, suppositions, dual-processes with suppositions, and probabilities. Most theories aim to conclude whether a certain inference form is accepted or not. However, present day research and experiments concentrate on endorsements -- in the example above, instead of a reasoner concluding whether "he has a fever" or not, they determine how likely is it that "he has a fever" by giving a probabilistic endorsement in the range 0-100. We are interested in examining whether and how cognitive theories can be adapted to model such endorsements, which will be one of the goals of the present seminar.

 

The seminar is a block seminar. The seminar will be organized online.

Background Literature (use VPN and get access through your University Freiburg account):

Schedule:

  • Organizational meeting (via Zoom) Friday, April 23rd at 12:00 
    (please mail your name and interest in participation no later than May 11th to the organizer)

  • Midterm presentation (via Zoom) Friday, June 11th from 12:00-14:00 

  • Seminar presentation (Zoom) July 9th from 9-17 and July 10th from 9-17

Requirements

  • Presentation of your preliminary & final results
    • Theoretical and computational foundation
    • Predictive performance
    • Ideas for improvement
  • Written report of your work (~6 pages, CogSci format)
    • Introduction/Motivation
    • Theoretical Foundation
    • Method/Model
    • Results
    • Conclusion/Discussion

Materials

  •  Introduction Meeting (Presentation will be uploaded)