403 research outputs found
Verification of Generalized Inconsistency-Aware Knowledge and Action Bases (Extended Version)
Knowledge and Action Bases (KABs) have been put forward as a semantically
rich representation of a domain, using a DL KB to account for its static
aspects, and actions to evolve its extensional part over time, possibly
introducing new objects. Recently, KABs have been extended to manage
inconsistency, with ad-hoc verification techniques geared towards specific
semantics. This work provides a twofold contribution along this line of
research. On the one hand, we enrich KABs with a high-level, compact action
language inspired by Golog, obtaining so called Golog-KABs (GKABs). On the
other hand, we introduce a parametric execution semantics for GKABs, so as to
elegantly accomodate a plethora of inconsistency-aware semantics based on the
notion of repair. We then provide several reductions for the verification of
sophisticated first-order temporal properties over inconsistency-aware GKABs,
and show that it can be addressed using known techniques, developed for
standard KABs
Synthesizing and executing plans in Knowledge and Action Bases
We study plan synthesis for a variant of Knowledge and Action Bases (KABs). KABs have been recently introduced as a rich, dynamic framework where states are full-fledged description logic (DL) knowledge bases (KBs) whose extensional part is manipulated by actions that can introduce new objects from an infinite domain. We show that, in general, plan existence over KABs is undecidable even under severe restrictions. We then focus on the class of state-bounded KABs, for which plan existence is decidable, and we provide sound and complete plan synthesis algorithms, through a novel combination of techniques based on standard planning, DL query answering, and finite-state abstractions. All results hold for any DL with decidable query answering. We finally show that for lightweight DLs, plan synthesis can be compiled into standard ADL planning. © 2016, CEUR-WS. All rights reserved
Reasoning about Explanations for Negative Query Answers in DL-Lite
In order to meet usability requirements, most logic-based applications
provide explanation facilities for reasoning services. This holds also for
Description Logics, where research has focused on the explanation of both TBox
reasoning and, more recently, query answering. Besides explaining the presence
of a tuple in a query answer, it is important to explain also why a given tuple
is missing. We address the latter problem for instance and conjunctive query
answering over DL-Lite ontologies by adopting abductive reasoning; that is, we
look for additions to the ABox that force a given tuple to be in the result. As
reasoning tasks we consider existence and recognition of an explanation, and
relevance and necessity of a given assertion for an explanation. We
characterize the computational complexity of these problems for arbitrary,
subset minimal, and cardinality minimal explanations
- …