{"title":"Dyadic Existential Rules","authors":"GEORG GOTTLOB, MARCO MANNA, CINZIA MARTE","doi":"10.1017/s1471068423000327","DOIUrl":null,"url":null,"abstract":"Abstract Existential rules form an expressive ${{\\textsf{Datalog}}}$ -based language to specify ontological knowledge. The presence of existential quantification in rule-heads, however, makes the main reasoning tasks undecidable. To overcome this limitation, in the last two decades, a number of classes of existential rules guaranteeing the decidability of query answering have been proposed. Unfortunately, only some of these classes fully encompass ${{\\textsf{Datalog}}}$ and, often, this comes at the price of higher computational complexity. Moreover, expressive classes are typically unable to exploit tools developed for classes exhibiting lower expressiveness. To mitigate these shortcomings, this paper introduces a novel general syntactic condition that allows us to define, systematically and in a uniform way, from any decidable class $\\mathcal{C}$ of existential rules, a new class called ${{\\textsf{Dyadic-}\\mathcal{C}}}$ enjoying the following properties: ( i ) it is decidable; ( ii ) it generalizes ${{\\textsf{Datalog}}}$ ; ( iii ) it generalizes $\\mathcal{C}$ ; ( iv ) it can effectively exploit any reasoner for query answering over $\\mathcal{C}$ ; and ( v ) its computational complexity does not exceed the highest between the one of $\\mathcal{C}$ and the one of ${{\\textsf{Datalog}}}$ .","PeriodicalId":49436,"journal":{"name":"Theory and Practice of Logic Programming","volume":"20 1","pages":"0"},"PeriodicalIF":1.4000,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Theory and Practice of Logic Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/s1471068423000327","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Existential rules form an expressive ${{\textsf{Datalog}}}$ -based language to specify ontological knowledge. The presence of existential quantification in rule-heads, however, makes the main reasoning tasks undecidable. To overcome this limitation, in the last two decades, a number of classes of existential rules guaranteeing the decidability of query answering have been proposed. Unfortunately, only some of these classes fully encompass ${{\textsf{Datalog}}}$ and, often, this comes at the price of higher computational complexity. Moreover, expressive classes are typically unable to exploit tools developed for classes exhibiting lower expressiveness. To mitigate these shortcomings, this paper introduces a novel general syntactic condition that allows us to define, systematically and in a uniform way, from any decidable class $\mathcal{C}$ of existential rules, a new class called ${{\textsf{Dyadic-}\mathcal{C}}}$ enjoying the following properties: ( i ) it is decidable; ( ii ) it generalizes ${{\textsf{Datalog}}}$ ; ( iii ) it generalizes $\mathcal{C}$ ; ( iv ) it can effectively exploit any reasoner for query answering over $\mathcal{C}$ ; and ( v ) its computational complexity does not exceed the highest between the one of $\mathcal{C}$ and the one of ${{\textsf{Datalog}}}$ .
期刊介绍:
Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.