Most Probable Explanation in Probabilistic Answer Set Programming

Azzolini, Damiano; Mazzotta, Giuseppe; Ricca, Francesco; Riguzzi, Fabrizio

doi:10.24963/ijcai.2025/1006

Most Probable Explanation in Probabilistic Answer Set Programming

Damiano Azzolini, Giuseppe Mazzotta, Francesco Ricca, Fabrizio Riguzzi

Download BibTeX Cite

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 9049-9057.

https://doi.org/10.24963/ijcai.2025/1006

Keywords

Uncertainty in AI: UAI: Uncertainty representations
Uncertainty in AI: UAI: Statistical relational AI
Knowledge Representation and Reasoning: KRR: Learning and reasoning
Knowledge Representation and Reasoning: KRR: Non-monotonic reasoning

Abstract

Most Probable Explanation (MPE) is a fundamental problem in statistical relational artificial intelligence.

In the context of Probabilistic Answer Set Programming (PASP), solving MPE is still an open research problem.

In this paper, we present three novel approaches for solving the MPE task in PASP that are based on: i) Algebraic Model Counting, ii) Answer Set Programming (ASP), and iii) ASP with quantifiers (ASP(Q)).

These approaches are implemented and evaluated against existing solvers across different datasets and configurations.

Empirical results demonstrate that the novel solutions consistently outperform existing alternatives for non-stratified programs.

Damiano Azzolini, Giuseppe Mazzotta, Francesco Ricca, and Fabrizio Riguzzi. 2025. Most Probable Explanation in Probabilistic Answer Set Programming. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 9049–9057. https://doi.org/10.24963/ijcai.2025/1006

@inproceedings{ijcai2025p1006,
  title     = {Most Probable Explanation in Probabilistic Answer Set Programming},
  author    = {Azzolini, Damiano and Mazzotta, Giuseppe and Ricca, Francesco and Riguzzi, Fabrizio},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {9049--9057},
  year      = {2025},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2025/1006},
  url       = {https://doi.org/10.24963/ijcai.2025/1006},
}

TY  - CPAPER
TI  - Most Probable Explanation in Probabilistic Answer Set Programming
AU  - Azzolini, Damiano
AU  - Mazzotta, Giuseppe
AU  - Ricca, Francesco
AU  - Riguzzi, Fabrizio
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 9049
EP  - 9057
DO  - 10.24963/ijcai.2025/1006
UR  - https://doi.org/10.24963/ijcai.2025/1006
ER  -