Enumerating Preferred Extensions: A Case Study of Human Reasoning

Alice Toniolo*, Timothy J. Norman, Nir Oren

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

3 Citations (Scopus)
9 Downloads (Pure)

Abstract

This paper seeks to better understand the links between human reasoning and preferred extensions as found within formal argumentation, especially in the context of uncertainty. The degree of believability of a conclusion may be associated with the number of preferred extensions in which the conclusion is credulously accepted. We are interested in whether people agree with this evaluation. A set of experiments with human participants is presented to investigate the validity of such an association. Our results show that people tend to agree with the outcome of a version of Thimm’s probabilistic semantics in purely qualitative domains as well as in domains in which conclusions express event likelihood. Furthermore, we are able to characterise this behaviour: the heuristics employed by people in understanding preferred extensions are similar to those employed in understanding probabilities.
Original languageEnglish
Title of host publicationTheory and Applications of Formal Argumentation
Subtitle of host publicationTAFA 2017
EditorsE Black, S Modgil, N Oren
Place of PublicationCham
PublisherSpringer Verlag
Pages192-210
Number of pages19
ISBN (Print)9783319755526
DOIs
Publication statusPublished - 2018
Event4th International Workshop on Theory and Applications of Formal Argumentation, TAFA 2017: (TAFA 2017) - Melbourne, Australia
Duration: 19 Aug 201720 Aug 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10757 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Workshop on Theory and Applications of Formal Argumentation, TAFA 2017
Country/TerritoryAustralia
CityMelbourne
Period19/08/1720/08/17

Keywords

  • Argumentation
  • Probabilistic semantics
  • User evaluation

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