Malmö University Publications
3637383940414239 of 151
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
Quest to Dungeon (QtD): Towards a Tool that Supports Collaboration between Narrative and Level Designers
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). (Game Lab)
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). (Game Lab)
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Sustainable Digitalisation Research Centre (SDRC). (Game Lab)ORCID iD: 0000-0002-7738-1601
2025 (English)In: EXAG-INT 2025: Experimental AI in Games and Intelligent Narrative Technologies 2025: Proceedings of the Joint AIIDE Workshops on Experimental AI in Games and Intelligent Narrative Technologies (EXAG-INT 2025) co-located with the 21st AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2025) Edmonton, Alberta, Canada, November 10-11, 2025., CEUR-WS , 2025, Vol. 4090Conference paper, Published paper (Refereed)
Abstract [en]

Quest to Dungeon (QtD) is a tool designed to bridge the gap between narrative design and procedural level generation in games, two processes that are typically developed in isolation from each other. QtD connects narrative design with level design by enabling designers to create quests by combining tasks in a grid interface, where each narrative task automatically generates corresponding dungeon rooms using task-specific algorithms. We evaluated QtD through a user study (N=8) where all participants created first a quest with two endings, and then a quest without constraints. Our results showed that participants found the tool intuitive and effective in visualizing how narrative objectives translate into level design. QtD helped enable faster iteration cycles for the participants, who speculated about its possible benefits for collaboration and communication between narrative and level designers.

Place, publisher, year, edition, pages
CEUR-WS , 2025. Vol. 4090
Series
Ceur Workshop Proceedings, E-ISSN 1613-0073
Keywords [en]
Challenges in Game Development, Procedural Content Generation, Quest Design, Quest-Driven Generation
National Category
Design
Identifiers
URN: urn:nbn:se:mau:diva-83976Scopus ID: 2-s2.0-105036885074OAI: oai:DiVA.org:mau-83976DiVA, id: diva2:2057164
Conference
2025 Joint AIIDE Workshops on Experimental AI in Games and Intelligent Narrative Technologies, EXAG-INT 2025, 10-11 Nov 2025, Alberta, Canada
Available from: 2026-05-04 Created: 2026-05-04 Last updated: 2026-05-04Bibliographically approved

Open Access in DiVA

fulltext(1104 kB)6 downloads
File information
File name FULLTEXT01.pdfFile size 1104 kBChecksum SHA-512
ffc14605fde6fb922f2d2589660690dc7494fb7e96a0f475401534b25248f1fdd2d417afb620d3f6b6f1af258dec8b51268c958cc5c300ad8814c8be0d013709
Type fulltextMimetype application/pdf

Other links

ScopusFulltext

Authority records

Alvarez, Alberto

Search in DiVA

By author/editor
Boutani, OscarShariati, SamAlvarez, Alberto
By organisation
Department of Computer Science and Media Technology (DVMT)Sustainable Digitalisation Research Centre (SDRC)
Design

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 67 hits
3637383940414239 of 151
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