English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

The provenance of modal inference

MPS-Authors
/persons/resource/persons214566

Hinterecker,  T
Project group: Social & Spatial Cognition, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Project group: Motion Perception & Simulation, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Ressource

Link
(Any fulltext)

Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Khemlani, S., Hinterecker, T., & Johnson-Laird, P. (2017). The provenance of modal inference. In G. Gunzelmann, A. Howes, T. Tenbrink, & E. Davelaar (Eds.), Computational Foundations of Cognition (pp. 663-668). Austin, TX, USA: Cognitive Science Society.


Cite as: http://hdl.handle.net/21.11116/0000-0000-C3AD-1
Abstract
People reason about possibilities routinely, and reasoners can infer “modal” conclusions, i.e., conclusions that concern what is possible or necessary, from premises that make no mention of modality. For instance, given that Cullen was born in New York or Kentucky, it is intuitive to infer that it’s possible that Cullen was born in New York, and a recent set of studies on modal reasoning bear out these intuitions (Hinterecker, Knauff, Johnson-Laird, 2016). What explains the tendency to make modal inferences? Conventional logic does not apply to modal reasoning, and so logicians invented many alternative systems of modal logic to capture valid modal inferences. But, none of those systems can explain the inference above. We posit a novel theory based on the idea that reasoners build mental models, i.e., iconic simulations of possibilities, when they reason about sentential connectives such as and, if, and or (Johnson-Laird, 2006). The theory posits that reasoners represent a set of conjunctive possibilities to capture the meanings of compound assertions. It is implemented in a new computational process model of sentential reasoning that can draw modal conclusions from non-modal premises. We describe the theory and computational model, and show how its performance matches reasoners’ inferences in two studies by Hinterecker et al. (2016). We conclude by discussing the model-based theory in light of alternative accounts of reasoning.