4,225 research outputs found
Belief Revision, Minimal Change and Relaxation: A General Framework based on Satisfaction Systems, and Applications to Description Logics
Belief revision of knowledge bases represented by a set of sentences in a
given logic has been extensively studied but for specific logics, mainly
propositional, and also recently Horn and description logics. Here, we propose
to generalize this operation from a model-theoretic point of view, by defining
revision in an abstract model theory known under the name of satisfaction
systems. In this framework, we generalize to any satisfaction systems the
characterization of the well known AGM postulates given by Katsuno and
Mendelzon for propositional logic in terms of minimal change among
interpretations. Moreover, we study how to define revision, satisfying the AGM
postulates, from relaxation notions that have been first introduced in
description logics to define dissimilarity measures between concepts, and the
consequence of which is to relax the set of models of the old belief until it
becomes consistent with the new pieces of knowledge. We show how the proposed
general framework can be instantiated in different logics such as
propositional, first-order, description and Horn logics. In particular for
description logics, we introduce several concrete relaxation operators tailored
for the description logic \ALC{} and its fragments \EL{} and \ELext{},
discuss their properties and provide some illustrative examples
Hypertableau Reasoning for Description Logics
We present a novel reasoning calculus for the description logic SHOIQ^+---a
knowledge representation formalism with applications in areas such as the
Semantic Web. Unnecessary nondeterminism and the construction of large models
are two primary sources of inefficiency in the tableau-based reasoning calculi
used in state-of-the-art reasoners. In order to reduce nondeterminism, we base
our calculus on hypertableau and hyperresolution calculi, which we extend with
a blocking condition to ensure termination. In order to reduce the size of the
constructed models, we introduce anywhere pairwise blocking. We also present an
improved nominal introduction rule that ensures termination in the presence of
nominals, inverse roles, and number restrictions---a combination of DL
constructs that has proven notoriously difficult to handle. Our implementation
shows significant performance improvements over state-of-the-art reasoners on
several well-known ontologies
Query inseparability by games
We investigate conjunctive query inseparability of description logic knowledge bases (KBs) with respect to a given signature, a fundamental problem for KB versioning, module extraction, forgetting and knowledge exchange. We develop a game-theoretic technique for checking query inseparability of KBs expressed in fragments of Horn-ALCHI, and show a number of complexity results ranging from P to ExpTime and 2ExpTime. We also employ our results to resolve two major open problems for OWL 2 QL by showing that TBox query inseparability and the membership problem for universal UCQ-solutions in knowledge exchange are both ExpTime-complete for combined complexity
Worst-case Optimal Query Answering for Greedy Sets of Existential Rules and Their Subclasses
The need for an ontological layer on top of data, associated with advanced
reasoning mechanisms able to exploit the semantics encoded in ontologies, has
been acknowledged both in the database and knowledge representation
communities. We focus in this paper on the ontological query answering problem,
which consists of querying data while taking ontological knowledge into
account. More specifically, we establish complexities of the conjunctive query
entailment problem for classes of existential rules (also called
tuple-generating dependencies, Datalog+/- rules, or forall-exists-rules. Our
contribution is twofold. First, we introduce the class of greedy
bounded-treewidth sets (gbts) of rules, which covers guarded rules, and their
most well-known generalizations. We provide a generic algorithm for query
entailment under gbts, which is worst-case optimal for combined complexity with
or without bounded predicate arity, as well as for data complexity and query
complexity. Secondly, we classify several gbts classes, whose complexity was
unknown, with respect to combined complexity (with both unbounded and bounded
predicate arity) and data complexity to obtain a comprehensive picture of the
complexity of existential rule fragments that are based on diverse guardedness
notions. Upper bounds are provided by showing that the proposed algorithm is
optimal for all of them
Reasoning over Ontologies with Hidden Content: The Import-by-Query Approach
There is currently a growing interest in techniques for hiding parts of the
signature of an ontology Kh that is being reused by another ontology Kv.
Towards this goal, in this paper we propose the import-by-query framework,
which makes the content of Kh accessible through a limited query interface. If
Kv reuses the symbols from Kh in a certain restricted way, one can reason over
Kv U Kh by accessing only Kv and the query interface. We map out the landscape
of the import-by-query problem. In particular, we outline the limitations of
our framework and prove that certain restrictions on the expressivity of Kh and
the way in which Kv reuses symbols from Kh are strictly necessary to enable
reasoning in our setting. We also identify cases in which reasoning is possible
and we present suitable import-by-query reasoning algorithms
Computing Horn Rewritings of Description Logics Ontologies
We study the problem of rewriting an ontology O1 expressed in a DL L1 into an
ontology O2 in a Horn DL L2 such that O1 and O2 are equisatisfiable when
extended with an arbitrary dataset. Ontologies that admit such rewritings are
amenable to reasoning techniques ensuring tractability in data complexity.
After showing undecidability whenever L1 extends ALCF, we focus on devising
efficiently checkable conditions that ensure existence of a Horn rewriting. By
lifting existing techniques for rewriting Disjunctive Datalog programs into
plain Datalog to the case of arbitrary first-order programs with function
symbols, we identify a class of ontologies that admit Horn rewritings of
polynomial size. Our experiments indicate that many real-world ontologies
satisfy our sufficient conditions and thus admit polynomial Horn rewritings.Comment: 15 pages. To appear in IJCAI-1
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