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Next: Consistency of - is Up: The Complexity of Reasoning Previous: Introduction

   
The Logic ALCQI

Definition 2.1   Let NC be a set of atomic concept names and NR be a set of atomic role names. Concepts in \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}} are built inductively from these using the following rules: all $A \in N_C$ are concepts, and, if C, C1, and C2 are concepts, then also

\begin{displaymath}\neg C, \ C_1 \sqcap C_2, \ \text{and} \ \ensuremath{(\geqslant n \; S \; C)} , \end{displaymath}

are concepts, where $n \in \mathbb{N} $ and S=R or S= R-1 for some $R \in N_R$. A cardinality restriction of \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}} is an expression of the form $(\geqslant n \ C)$ or $(\leqslant n \ C)$ where C is a concept and $n \in \mathbb{N} $; an \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}}- \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} 2 is a finite set of cardinality restrictions. The semantics of concepts is defined relative to an interpretation $\mathcal{I} = (\Delta^\mathcal{I},\cdot^\mathcal{I})$, which consists of a domain \ensuremath{\Delta^\mathcal{I}} and a valuation $(\cdot^\mathcal{I})$ that maps each concept name A to a subset $A^{\mathcal{I}}$ of \ensuremath{\Delta^\mathcal{I}} and each role name R to a subset $R^{\mathcal{I}}$ of $\ensuremath{\Delta^\mathcal{I}}\times \ensuremath{\Delta^\mathcal{I}} $. This valuation is inductively extended to arbitrary concepts using the following rules, where $\sharp M$ denotes the cardinality of a set M:

\begin{align*}(\neg C)^{\mathcal{I}} & := \ensuremath{\Delta^\mathcal{I}}\setmin... ...,a) \in R^{\mathcal{I}} \wedge b \in C^{\mathcal{I}} \} \geq n \}. \end{align*}


An interpretation $\mathcal{I}$ satisfies a cardinality restriction $(\geqslant n \ C)$ iff $\sharp (C^{\mathcal{I}}) \geq n$, and it satisfies $(\leqslant n \ C)$ iff $\sharp (C^{\mathcal{I}}) \leq n$. It satisfies a \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}}T iff it satisfies all cardinality restrictions in T; in this case, $\mathcal{I}$ is called a model of T and we will denote this fact by $\mathcal{I}\models T$. A \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} that has a model is called consistent. With \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}} we denote the fragment of \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}} that does not contain any inverse roles R-1.

Using the constructors from Definition 2.1, we use $(\forall \ C)$ as an abbreviation for the cardinality restriction $(\leqslant 0 \; \neg C)$ and introduce the following abbreviations for concepts:

\begin{displaymath}\begin{array}{r@{\;}c@{\;}l@{\qquad}r@{\;}c@{\;}l} C_1 \sqcu... ... S.C & = & \ensuremath{(\leqslant 0 \; S \; \neg C)}\end{array}\end{displaymath}

TBoxes consisting of cardinality restrictions have first been studied in [BBH96] for the DL \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}}. Obviously, two concepts C,D have the same extension in an interpretation $\mathcal{I}$ iff $\mathcal{I}$ satisfies the cardinality restriction $(\leqslant 0 \ (C \sqcap \neg D) \sqcup (\neg C \sqcap D))$. Hence, cardinality restrictions can express terminological axioms of the form C = D, which are satisfied by an interpretation $\mathcal{I}$ iff $C^\mathcal{I}= D^\mathcal{I}$. General axioms are the most expressive TBox formalisms usually studied in the DL context [DL96]. One standard inference service for DL systems is satisfiability of a concept C with respect to a \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} T, i.e., is there an interpretation $\mathcal{I}$ such that $\mathcal{I}\models T$ and $C^\mathcal{I}\neq \emptyset$. For a TBox formalism based on cardinality restrictions this is easily reduced to TBox consistency, because obviously C is satisfiable with respect to T iff $T \cup \{(\geqslant \ 1 \ C) \}$ is a consistent \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}}. For this the reason, we will restrict our attention to \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} consistency; other standard inferences such as concept subsumption can be reduced to consistency as well.


  
Figure 2: The translation from ALCQI into C2
\begin{figure} \begin{center} \framebox[\textwidth]{ $\begin{array}{l@{\;}c@{... ... \ C) \mid (\bowtie \ n \ C) \in T \} \end{array}$ } \end{center} \end{figure}

Until now there does not exist a direct decision procedure for \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}} \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} consistency. Nevertheless this problem can be decided with the help of a well-known translation of \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}}- \ensuremath {\text {T\hspace {-1pt}}_C\hspace {-1pt}\text {Boxes}} to \ensuremath{C^2} [Bor96], given in Figure 2. The logic \ensuremath{C^2} is the fragment of predicate logic in which formulae may contain at most two variables, but which is enriched with counting quantifiers of the form $\exists^{\geq \ell}$. The translation $\Psi$ yields a satisfiable sentence of \ensuremath{C^2} if and only if the translated \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} is consistent. Since the translation from \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}} to \ensuremath{C^2} can be performed in linear time, the \textsc{NExp\-Time} upper bound [GOR97,PST97] for satisfiability of \ensuremath{C^2} directly carries over to \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}}- \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}} consistency:

Lemma 2.2
Consistency of an \ensuremath{\mathcal{A}\!\mathcal{L}\!\mathcal{C}\!\mathcal{Q}\!\mathcal{I}}- \ensuremath{\text{T\hspace{-1pt}}_C\hspace{-1pt}\text{Box}}T can be decided in \textsc{NExp\-Time}.

Please note that the \textsc{NExp\-Time}-completeness result from [PST97] is only valid if we assume unary coding of numbers in the input; this implies that a number n may not be stored in logarithmic space in some k-ary representation but consumes n units of storage. This is the standard assumption made by most results concerning the complexity of DLs. We will come back to this issue in Section 3.3.


next up previous
Next: Consistency of - is Up: The Complexity of Reasoning Previous: Introduction

Stephan Tobies
May 02 2000