Probabilistic semantic automata in the verification of quantified statements

Open Access
Authors
Publication date 2014
Host editors
  • P. Bello
  • M. Guarini
  • M. McShane
  • B. Scassellati
Book title CogSci 2014
Book subtitle cognitive science meets artificial intelligence: human and artifical agents in interactive contexts: 36th Annual Cognitive Science Conference: Quebec City, Canada, Jul 23-Jul 26
ISBN (electronic)
  • 9780991196708
Event 36th Annual Meeting of the Cognitive Science Society
Volume | Issue number 4
Pages (from-to) 2967-2972
Publisher Austin, TX: Cognitive Science Society
Organisations
  • Faculty of Humanities (FGw)
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
Strategies used by people to verify quantified sentences, like `Most cars are white', have been a popular research topic on the intersection of linguistics, computer science, philosophy, and psychology. A prominent computational model of the task, semantic automata, has been introduced by van Benthem in 1983. In this paper we present a probabilistic extension of the model. We show that the model explains counting errors in the verification process. Furthermore, we observe that the variation in quantifier verification data cannot be explained by Approximate Number Sense, a prominent approach to probabilistic number estimation.
Document type Conference contribution
Language English
Published at https://mindmodeling.org/cogsci2014/papers/512/
Other links https://cogsci.mindmodeling.org/2014/
Downloads
paper512 (Final published version)
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