A New Probabilistic Explanation of the Modus Ponens–Modus Tollens Asymmetry

In CogSci 2019 Proceedings. Montreal, Québec, Kanada: pp. 289–294 (2019)
Download Edit this record How to cite View on PhilPapers
Abstract
A consistent finding in research on conditional reasoning is that individuals are more likely to endorse the valid modus ponens (MP) inference than the equally valid modus tollens (MT) inference. This pattern holds for both abstract task and probabilistic task. The existing explanation for this phenomenon within a Bayesian framework (e.g., Oaksford & Chater, 2008) accounts for this asymmetry by assuming separate probability distributions for both MP and MT. We propose a novel explanation within a computational-level Bayesian account of reasoning according to which “argumentation is learning”. We show that the asymmetry must appear for certain prior probability distributions, under the assumption that the conditional inference provides the agent with new information that is integrated into the existing knowledge by minimizing the Kullback-Leibler divergence between the posterior and prior probability distribution. We also show under which conditions we would expect the opposite pattern, an MT-MP asymmetry
Keywords
No keywords specified (fix it)
Categories
(categorize this paper)
PhilPapers/Archive ID
HARANP-5
Upload history
Archival date: 2020-10-06
View other versions
Added to PP index
2020-04-19

Total views
26 ( #56,138 of 58,310 )

Recent downloads (6 months)
13 ( #43,715 of 58,310 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.