ASP(Q) for Inconsistent Prioritized Data Handling
A new study available on arXiv (2604.21603) explores how answer set programming (ASP) and its quantifier extension, ASP(Q), can be used to query data that has priorities and inconsistencies. The researchers look into how priority relationships among conflicting facts can help create three types of optimal repairs: Pareto, globally optimal, and completion-optimal. They analyze different semantics, such as AR, brave, and IAR, finding that the complexity of query answering often falls within the first or second level of the polynomial hierarchy across various logical theories. This paper also presents the first implementation of globally-optimal repair-based semantics, which provides a manageable under-approximation of all optimal repair semantics, and includes an experiment on its feasibility and impact.
Key facts
- Paper arXiv:2604.21603 uses ASP and ASP(Q) for inconsistent prioritized data.
- Three optimal repair types defined: Pareto-, globally-, and completion-optimal.
- Variants of AR, brave, and IAR semantics are considered.
- Query answering complexity is in first or second level of polynomial hierarchy.
- First implementation of globally-optimal repair-based semantics.
- First implementation of grounded semantics as tractable under-approximation.
- Experimental evaluation on feasibility of globally-optimal repair semantics.
- Impact of different semantics is evaluated.
Entities
Institutions
- arXiv