Eiter, T., & Geibinger, T. (2023). Explaining Answer-Set Programs with Abstract Constraint Atoms. In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23) (pp. 3193–3202). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/356
E192-03 - Forschungsbereich Knowledge Based Systems
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Published in:
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI-23)
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ISBN:
978-1-956792-03-4
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Date (published):
Aug-2023
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Event name:
Thirty-Second International Joint Conference on Artificial Intelligence
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Event date:
19-Aug-2023 - 25-Aug-2023
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Event place:
Macau, China
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Number of Pages:
10
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Publisher:
International Joint Conferences on Artificial Intelligence
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Peer reviewed:
Yes
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Keywords:
Knowledge Representation And Reasoning (KRR); Logic Programming; Computational Complexity of Reasoning
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Abstract:
Answer-Set Programming (ASP) is a popular declarative reasoning and problem solving formalism. Due to the increasing interest in explainabilty, several explanation approaches have been developed for ASP. However, support for commonly used advanced language features of ASP, as for example aggregates or choice rules, is still mostly lacking. We deal with explaining ASP programs containing Abstract Constraint Atoms, which encompass the above features and others. We provide justifications for the presence, or absence, of an atom in a given answer-set. To this end, we introduce several formal notions of justification in this setting based on the one hand on a semantic characterisation utilising minimal partial models, and on the other hand on a more ruled-guided approach. We provide complexity results for checking and computing such justifications, and discuss how the semantic and syntactic approaches relate and can be jointly used to offer more insight. Our results contribute to a basis for explaining commonly used language features and thus increase accessibility and usability of ASP as an AI tool.
