hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Why Bad Coffee? Explaining BDI Agent Behaviour with Valuings (Extended Abstract)
Victoria University Of Wellington, Wellington, New Zealand.
Halmstad University, School of Information Technology.ORCID iD: 0000-0001-8587-2251
Umeå University, Umea, Sweden.ORCID iD: 0000-0001-7409-5813
Umeå University, Umea, Sweden.
2022 (English)In: IJCAI International Joint Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, 2022, p. 5782-5786Conference paper, Published paper (Refereed)
Abstract [en]

An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results. © 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.

Place, publisher, year, edition, pages
Palo Alto, CA: AAAI Press, 2022. p. 5782-5786
Series
International Joint Conference on Artificial Intelligence. Proceedings, ISSN 1045-0823
National Category
Social Sciences Business Administration
Identifiers
URN: urn:nbn:se:hh:diva-48328Scopus ID: 2-s2.0-85137932084ISBN: 9781956792003 (print)OAI: oai:DiVA.org:hh-48328DiVA, id: diva2:1702522
Conference
31st International Joint Conference on Artificial Intelligence (IJCAI), Vienna, Austria, 23-29 July 2022
Available from: 2022-10-11 Created: 2022-10-11 Last updated: 2022-10-19Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records

Sidorenko, Galina

Search in DiVA

By author/editor
Sidorenko, GalinaDignum, Virginia
By organisation
School of Information Technology
Social SciencesBusiness Administration

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 24 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf