Marco Ragni

Why the average reasoner does not exist: Cognitive models of the individual reasoner

DIAS Fellow

Marco Ragni
11/11 2020
12:15-13:15, on Zoom

Associate Professor Marco Ragni has a keen interest in the specifics of how the human mind process information and how this differs from formal and computational approaches. He holds two Ph.Ds.; Computer Science (2008) and Cognitive Science (2013) from the University of Freiburg.

He has contributed as Board Member at Special Research Center “Spatial Cognition” and as Chief Executive of the Cognition-Section within the Artificial Intelligence Section of the German Society of Informatics (GI).

Marco Ragni was Head of the Cognitive Computation Lab at University Freiburg. He was awarded in 2015 with the prestigious Heisenberg-Fellowship from the Deutsche Forschungsgemeinschaft (DFG) for researching “Formalization, Modeling and Implementation of a neurocognitive theory of deductive reasoning”.


Like they do today with other humans, humans might be soon reasoning collaboratively with AI systems. For this to happen, however, AI systems need to be able to “understand” the specifics of the human reasoning process.

It is not sufficient to implement in computational systems the normative laws of “correct reasoning” such as classical logic or probability theory by expecting that in general humans will employ them.

Whenever humans reason about information, their derived conclusions can significantly deviate from normative theories. This is, however, not caused by simple errors of attention or motivation, but it depends on the specific way about how humans represent information mentally.

Despite progress of psychological theories, a descriptive theory of human reasoning in general and for individual reasoners’ is still missing. But what are the characteristics of human reasoning? How do we need to change psychological experimental research to better understand human reasoning and how good are state-of-the-art cognitive systems to predict an individual reasoner? How can we improve predictive models?

Implications for human reasoning and cognitive systems are discussed.

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Please note that the Idea will be held on Zoom only due to the current COVID-19 restrictions.