Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.23101 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912104141815808 |
|---|---|
| author | Bazzaz, Mahsa Cooper, Seth |
| author_facet | Bazzaz, Mahsa Cooper, Seth |
| contents | Procedurally generated levels created by machine learning models can be unsolvable without further editing. Various methods have been developed to automatically repair these levels by enforcing hard constraints during the post-processing step. However, as levels increase in size, these constraint-based repairs become increasingly slow. This paper proposes using explainability methods to identify specific regions of a level that contribute to its unsolvability. By assigning higher weights to these regions, constraint-based solvers can prioritize these problematic areas, enabling more efficient repairs. Our results, tested across three games, demonstrate that this approach can help to repair procedurally generated levels faster. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_23101 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Guided Game Level Repair via Explainable AI Bazzaz, Mahsa Cooper, Seth Artificial Intelligence Machine Learning Procedurally generated levels created by machine learning models can be unsolvable without further editing. Various methods have been developed to automatically repair these levels by enforcing hard constraints during the post-processing step. However, as levels increase in size, these constraint-based repairs become increasingly slow. This paper proposes using explainability methods to identify specific regions of a level that contribute to its unsolvability. By assigning higher weights to these regions, constraint-based solvers can prioritize these problematic areas, enabling more efficient repairs. Our results, tested across three games, demonstrate that this approach can help to repair procedurally generated levels faster. |
| title | Guided Game Level Repair via Explainable AI |
| topic | Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2410.23101 |