2011/04/06 by Manuel Bodirsky, Martin Hils, Bodirsky, Manuel +3
Computer Science · #Artificial Intelligence (cs.AI) #Computational Complexity (cs.CC) #Constraint Satisfaction and Optimization #F.2.2 #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Semantic Web and Ontologies
paper · doi:10.48550/arxiv.1104.1045
openalex publication_date 2011/04/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Many fundamental problems in artificial intelligence, knowledge representation, and verification involve reasoning about sets and relations between sets and can be modeled as set constraint satisfaction problems (set CSPs). Such problems are frequently intractable, but there are several important set CSPs that are known to be polynomial-time tractable. We introduce a large class of set CSPs that can be solved in quadratic time. Our class, which we call EI, contains all previously known tractable set CSPs, but also some new ones that are of crucial importance for example in description logics. The class of EI set constraints has an elegant universal-algebraic characterization, which we use to show that every set constraint language that properly contains all EI set constraints already has a finite sublanguage with an NP-hard constraint satisfaction problem.