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http://bura.brunel.ac.uk/handle/2438/28017Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Fukaya, K | - |
| dc.contributor.author | Daylamani-Zad, D | - |
| dc.contributor.author | Agius, H | - |
| dc.date.accessioned | 2024-01-15T15:38:36Z | - |
| dc.date.available | 2024-01-15T15:38:36Z | - |
| dc.date.issued | 2026-03-04 | - |
| dc.identifier | ORCiD: Kaisei Fukaya https://orcid.org/0000-0001-9828-7641 | - |
| dc.identifier | ORCiD: Damon Daylamani-Zad https://orcid.org/0000-0001-7849-458X | - |
| dc.identifier | ORCiD: Harry Agius https://orcid.org/0000-0002-8818-2683 | - |
| dc.identifier.citation | Fukaya, K., Daylamani-Zad, D. and Agius, H. (2026) 'Heuristics for AI-Driven Graphical Asset Generation Tools in Game Design and Development Pipelines: A User-Centered Approach', International Journal of Human-Computer Interaction, 0 (ahead of print), pp. 1–22. doi: 10.1080/10447318.2026.2632170. | en-US |
| dc.identifier.issn | 1044-7318 | - |
| dc.identifier.other | arXiv:2503.02703v2 [cs.HC] | - |
| dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/28017 | - |
| dc.description | Supplemental material is available online at: https://www.tandfonline.com/doi/full/10.1080/10447318.2026.2632170# . | en-US |
| dc.description | A preprint version of the article is available under a CC BY licence at arXiv:2503.02703v2 [cs.HC] (https://arxiv.org/abs/2503.02703). [v2] Fri, 27 Jun 2025 16:11:20 UTC (861 KB) . It has not been certified by peer review. | en-US |
| dc.description.abstract | Graphical assets play an important role in design and development of games. There is potential in the use of AI-driven generative tools to aid in creation of such assets, improving pipelines. However, there is little research to address how generative methods can fit into the wider pipeline, and no guidelines or heuristics for creating such tools. Hence, we conducted a user study with 16 game designers and developers to examine their behaviour and interaction with such tools. Findings highlight that early design stage is preferred by all participants. Designers and developers prioritise rapid variations over initial quality of assets. Results also strongly raised the need for better integration of such tools in existing design/development environments and pipelines, specifically regarding common data formats and output manipulability. Informed by these results, we provide a set of heuristics for creating tools that meet the expectations and needs of game designers and developers. | en-US |
| dc.format.extent | 1–22 | - |
| dc.format.medium | Print-Electronic | - |
| dc.publisher | Taylor and Francis | - |
| dc.relation.uri | https://arxiv.org/abs/2503.02703 | - |
| dc.rights | Creative Commons Attribution 4.0 International | - |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
| dc.subject | graphical game assets | en-US |
| dc.subject | artificial Intelligence | en-US |
| dc.subject | PCG | en-US |
| dc.subject | user behaviour | en-US |
| dc.subject | user interface | en-US |
| dc.title | Heuristics for AI-Driven Graphical Asset Generation Tools in Game Design and Development Pipelines: A User-Centered Approach | - |
| dc.type | Journal Article | - |
| dc.date.dateAccepted | 2026-02-10 | - |
| dc.identifier.doi | https://doi.org/10.1080/10447318.2026.2632170 | - |
| dc.relation.isPartOf | International Journal of Human-Computer Interaction | - |
| pubs.issue | 0 | - |
| pubs.publication-status | Published online | - |
| pubs.volume | 00 | - |
| dc.identifier.eissn | 1532-7590 | - |
| dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
| dcterms.dateAccepted | 2026-02-10 | - |
| dc.rights.holder | The Author(s) | - |
| dc.contributor.orcid | Fukaya, Kaisei [0000-0001-9828-7641] | - |
| dc.contributor.orcid | Daylamani-Zad, Damon [0000-0001-7849-458X] | - |
| dc.contributor.orcid | Agius, Harry [0000-0002-8818-2683] | - |
| Appears in Collections: | Brunel Design School Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | Copyright © 2026 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. | 3.77 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License
