An XAI View on Explainable ASP: Methods, Systems, and Perspectives
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917215026020352 |
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| author | Eiter, Thomas Geibinger, Tobias Saribatur, Zeynep G. |
| author_facet | Eiter, Thomas Geibinger, Tobias Saribatur, Zeynep G. |
| contents | Answer Set Programming (ASP) is a popular declarative reasoning and problem solving approach in symbolic AI. Its rule-based formalism makes it inherently attractive for explainable and interpretive reasoning, which is gaining importance with the surge of Explainable AI (XAI). A number of explanation approaches and tools for ASP have been developed, which often tackle specific explanatory settings and may not cover all scenarios that ASP users encounter. In this survey, we provide, guided by an XAI perspective, an overview of types of ASP explanations in connection with user questions for explanation, and describe how their coverage by current theory and tools. Furthermore, we pinpoint gaps in existing ASP explanations approaches and identify research directions for future work. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_14764 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An XAI View on Explainable ASP: Methods, Systems, and Perspectives Eiter, Thomas Geibinger, Tobias Saribatur, Zeynep G. Artificial Intelligence Human-Computer Interaction Logic in Computer Science Answer Set Programming (ASP) is a popular declarative reasoning and problem solving approach in symbolic AI. Its rule-based formalism makes it inherently attractive for explainable and interpretive reasoning, which is gaining importance with the surge of Explainable AI (XAI). A number of explanation approaches and tools for ASP have been developed, which often tackle specific explanatory settings and may not cover all scenarios that ASP users encounter. In this survey, we provide, guided by an XAI perspective, an overview of types of ASP explanations in connection with user questions for explanation, and describe how their coverage by current theory and tools. Furthermore, we pinpoint gaps in existing ASP explanations approaches and identify research directions for future work. |
| title | An XAI View on Explainable ASP: Methods, Systems, and Perspectives |
| topic | Artificial Intelligence Human-Computer Interaction Logic in Computer Science |
| url | https://arxiv.org/abs/2601.14764 |