---
title: "AMO-aware Aggregates in Answer Set Programming"
authors:
  - "Mario Alviano"
  - "Carmine Dodaro"
  - "Salvatore Fiorentino"
  - "Marco Maratea"
doi: "10.24963/ijcai.2024/356"
url: "https://ijcai.org/proceedings/2024/356"
pdf: "https://ijcai.org/proceedings/2024/0356.pdf"
venue: "Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence"
year: 2024
pages: "3215-3223"
track: "Main Track"
keywords:
  - "Knowledge Representation and Reasoning: KRR: Non-monotonic reasoning"
  - "Knowledge Representation and Reasoning: KRR: Logic programming"
---

# AMO-aware Aggregates in Answer Set Programming

Mario Alviano, Carmine Dodaro, Salvatore Fiorentino, Marco Maratea

*Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence*, pages 3215-3223. DOI: [10.24963/ijcai.2024/356](https://doi.org/10.24963/ijcai.2024/356)

## Abstract

Aggregates such as sum and count are among the most frequently used linguistic extensions of Answer Set Programming (ASP).
At-most-one (AMO) constraints are a specific form of aggregates that excludes the simultaneous truth of multiple elements in a set.
This article unleashes a powerful propagation strategy in case groups of elements in an aggregate are also involved in AMO constraints.
In fact, the combined knowledge given by aggregates and AMO constraints significantly increases the effectiveness of search space pruning, resulting in sensible performance gains.