Abductive Logic Programming for Normative Reasoning and Ontologies

摘要

Abductive Logic Programming (ALP) has been exploited to formalize societies of agents, commitments and norms, taking advantage from ALP operational support as a (static or dynamic) verification tool. In [7], the most common deontic operators (obligation, prohibition, permission) are mapped into the abductive expectations, of an ALP framework for agent societies. Building upon such correspondence, in [5], authors introduced Deon~+, a language where obligation and prohibition deontic operators are enriched with quantification over time, by means of ALP and Constraint Logic Programming (CLP). In recent work [30,31], we have shown that the same ALP framework can be suitable to represent Datalog~± ontologies. Ontologies are a fundamental component of both the Semantic Web and knowledge-based systems, even in the legal setting, since they provide a formal and machine manipulable model of a domain. In this work, we show that ALP is a suitable framework for representing both norms and ontologies. Normative reasoning and ontological query answering are obtained by applying the same abductive proof procedure, smoothly achieving their integration. In particular, we consider the ALP framework named SCIFF and derived from the IFF abductive framework, able to deal with existentially (and universally) quantified variables in rule heads and CLP constraints. The main advantage is that this integration is achieved within a single language, grounded on abduction in computational logic.