scholarly journals Tightly Coupled Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web

2010 ◽  
pp. 237-256 ◽  
Author(s):  
Thomas Lukasiewicz ◽  
Umberto Straccia
Keyword(s):  
Query Processing ◽  
Description Logic ◽  
Description Logics ◽  
Logic Programs ◽  
New Formalism ◽  
Disjunctive Logic Programs ◽  
Tightly Coupled ◽  
Answer Set Semantics ◽  
Fuzzy Description ◽  
Answer Set

This chapter presents a novel approach to fuzzy description logic programs (or simply fuzzy dl-programs) under the answer set semantics, which is a tight integration of fuzzy disjunctive logic programs under the answer set semantics with fuzzy description logics. From a different perspective, it is a generalization of tightly coupled disjunctive dl-programs by fuzzy vagueness in both the description logic and the logic program component. The authors show that the new formalism faithfully extends both fuzzy disjunctive logic programs and fuzzy description logics, and that under suitable assumptions, reasoning in the new formalism is decidable. The authors present a polynomial reduction of certain fuzzy dl-programs to tightly coupled disjunctive dl-programs, and we analyze the complexity of consistency checking and query processing for certain fuzzy dl-programs. Furthermore, the authors provide a special case of fuzzy dl-programs for which deciding consistency and query processing can both be done in polynomial time in the data complexity.

scholarly journals Loop formulas for description logic programs

2010 ◽  
Vol 10 (4-6) ◽  
pp. 531-545 ◽  
Author(s):  
YISONG WANG ◽  
JIA-HUAI YOU ◽  
LI YAN YUAN ◽  
YI-DONG SHEN
Keyword(s):  
Semantic Web ◽  
Description Logic ◽  
Description Logics ◽  
Answer Set Programming ◽  
Desirable Property ◽  
Logic Programs ◽  
Alternative Semantics ◽  
Answer Set Semantics ◽  
Answer Sets ◽  
Answer Set

AbstractDescription Logic Programs (dl-programs) proposed by Eiter et al. constitute an elegant yet powerful formalism for the integration of answer set programming with description logics, for the Semantic Web. In this paper, we generalize the notions of completion and loop formulas of logic programs to description logic programs and show that the answer sets of a dl-program can be precisely captured by the models of its completion and loop formulas. Furthermore, we propose a new, alternative semantics for dl-programs, called the canonical answer set semantics, which is defined by the models of completion that satisfy what are called canonical loop formulas. A desirable property of canonical answer sets is that they are free of circular justifications. Some properties of canonical answer sets are also explored.

scholarly journals Determining Inference Semantics for Disjunctive Logic Programs (Extended Abstract)

2020 ◽  
Author(s):  
Yi-Dong Shen ◽  
Thomas Eiter
Keyword(s):  
Minimal Model ◽  
Logic Programs ◽  
Disjunctive Logic Programs ◽  
Answer Set Semantics ◽  
Answer Sets ◽  
Answer Set

[Gelfond and Lifschitz, 1991] introduced simple disjunctive logic programs and defined the answer set semantics called GL-semantics. We observed that the requirement of GL-semantics, i.e., an answer set should be a minimal model of the GL-reduct may be too strong and exclude some answer sets that would be reasonably acceptable. To address this, we present a novel and more permissive semantics, called determining inference semantics.

scholarly journals Sound and Complete Inference Rules for SE-Consequence

2008 ◽  
Vol 31 ◽  
pp. 205-216 ◽  
Author(s):  
K. Wong
Keyword(s):  
Logic Program ◽  
Inference Rules ◽  
Logic Programs ◽  
Consequence Relation ◽  
Disjunctive Logic Programs ◽  
Complete Set ◽  
Answer Set Semantics ◽  
Answer Set

The notion of strong equivalence on logic programs with answer set semantics gives rise to a consequence relation on logic program rules, called SE-consequence. We present a sound and complete set of inference rules for SE-consequence on disjunctive logic programs.

scholarly journals Capability-oriented architectural analysis method based on fuzzy description logic

2016 ◽  
Vol 13 (1) ◽  
pp. 287-308 ◽  
Author(s):  
Zhang Tingting ◽  
Liu Xiaoming ◽  
Wang Zhixue ◽  
Dong Qingchao
Keyword(s):  
Business Strategy ◽  
Domain Knowledge ◽  
Description Logic ◽  
Description Logics ◽  
Model Verification ◽  
Architectural Analysis ◽  
Requirements Modeling ◽  
Strategy Model ◽  
Domain Specific Modeling ◽  
Fuzzy Description

A number of problems may arise from architectural requirements modeling, including alignment of it with business strategy, model integration and handling the uncertain and vague information. The paper introduces a method for modeling architectural requirements in a way of ontology-based and capability-oriented requirements elicitation. The requirements can be modeled within a three-layer framework. The Capability Meta-concept Framework is provided at the top level. The domain experts can capture the domain knowledge within the framework, forming the domain ontology at the second level. The domain concepts can be used for extending the UML to produce a domain-specific modeling language. A fuzzy UML is introduced to model the vague and uncertain features of the capability requirements. An algorithm is provided to transform the fuzzy UML models into the fuzzy Description Logics ontology for model verification. A case study is given to demonstrate the applicability of the method.

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