Abstract
It seems widely accepted that human reasoning cannot be modeled by means of classical logic. Psychological experiments have repeatedly shown that participants’ answers systematically deviate from the classical logically correct answers. Recently, a new computational logic approach to modeling human syllogistic reasoning has been developed which seems to perform better than other state-of-the-art cognitive theories. We take this approach as starting point, yet instead of trying to model the human reasoner, we aim at identifying clusters of reasoners, which can be characterized by reasoning principles or by heuristic strategies.
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Notes
- 1.
Under WCS, the negative assumption will become \(A \leftrightarrow \bot \) and, hence, A has to be false. This can, however, be overwritten by other rules and facts (defeating the assumption).
- 2.
For n principles, there are up to \(2^n\) possible clusters. Additionally, it is unknown if the current set of principles is already complete.
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Dietz Saldanha, EA., Hölldobler, S., Mörbitz, R. (2018). The Syllogistic Reasoning Task: Reasoning Principles and Heuristic Strategies in Modeling Human Clusters. In: Seipel, D., Hanus, M., Abreu, S. (eds) Declarative Programming and Knowledge Management. WFLP WLP INAP 2017 2017 2017. Lecture Notes in Computer Science(), vol 10997. Springer, Cham. https://doi.org/10.1007/978-3-030-00801-7_10
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