2.8 Relation to Description Logics
2.8.3 The description logic ALE
In later chapters, we will also make reference to the description logic ALE, which is obtained from ALC by disallowing disjunction and general negation of concepts. Formally, the syntax of ALE concept expressions is defined recursively as follows:
C::= ⊤ | ⊥ | A | ¬A | C ⊓ C | ∀R.C | ∃R.C
Using the mappings between Kn and ALC from the previous subsection, we see that ALE expressions correspond precisely to the set of Kn formulae which are in negation normal form and do not contain any disjunction symbols.
The reduced expressiveness of ALE compared to ALC is rewarded by a drop in the complexity of reasoning: both the unsatisfiability and subsumption tasks5 for ALE concept expressions can be accomplished in non-deterministic polynomial time, whereas the corresponding problems for ALC are Pspace-complete.
Theorem 2.8.3 ([SSS91], [DLN+92]).
Unsatisfiability and subsumption of ALE concept expressions are both in NP. Proof. We give a proof for unsatisfiability, and refer the reader to [DLN+92] for subsumption. Consider the following non-deterministic procedure for deciding the unsatisfiability of an ALE concept C:
(1) Guess a (possibly empty) sequence S1, ..., Sn of subconcepts6 of C such that n≤ δ(C) and each Si is of the form ∃R.E. Set D equal to C.
5. For description logics like ALC which allow for full negation, concept satisfiability and sub- sumption can be reduced to one another, but for less expressive logics, these tasks can have different complexities.
6. The notion of subconcept is defined analogously to that of subformula. Likewise, the size and depth of a concept are defined in the same manner as for formulae.
58 2.8. Relation to Description Logics
(2) For i = 1 to n
If Si = ∃R.E is a conjunct of D,
Set D = E ⊓ (⊓F∈FF), where F = {F | ∀R.F is a conjunct of D} Else, return no
(3) Return yes if D has a conjunct ⊥ or a pair of conjuncts A, ¬A, else return no. This procedure clearly runs in non-deterministic polynomial time since in Step 1 we guess at most n ≤ |C| concepts each with size at most |C|, and there are at most n≤ |C| iterations of the for loop in Step 2, each iteration taking only a polynomial amount of time.
We now show that the above procedure outputs yes just in the case the input concept is unsatisfiable. For the first direction, suppose the output on C is yes, and let S1, ..., Sn be the sequence of subconcepts guessed in Step 1. It can be easily shown by induction that the concept D at the beginning of Step 3 must satisfy |= C ⊑ (∃R)nD. Moreover, we also know that D must have a conjunct ⊥ or a pair of conjuncts A and ¬A, since the output on C is yes. It follows that |= C ⊑ (∃R)n⊥, and hence |= C ⊑ ⊥. For the other direction, suppose C is unsatisfiable. We set D1 = C, and we construct a sequence of concepts S1, ..., Sm in the following manner. If at stage i, the concept Di has a conjunct ⊥ or a pair of conjuncts A and ¬A, we return the empty sequence. Otherwise, the concept Di must possess conjuncts ∃R.E, ∀R.F1, ..., ∀R.Fm such that E ⊓ F1⊓ ... ⊓ Fm is unsatisfiable. We set Si = ∃R.E and set Di+1 = E ⊓ F1⊓ ... ⊓ Fm. We remark that there can be at most δ(C) elements in the constructed sequence since the depth of Di+1 is at least one less than the depth of Di. We also remark that if the constructed sequence has n elements, then the concept Dn+1 has either a conjunct ⊥ or a pair of conjuncts A, ¬A. Moreover, it is easily verified that if the sequence of subconcepts we have constructed is guessed in Step 1, then the concept examined in Step 3 is precisely the concept Dn+1. It follows that there exists a sequence which leads to an output of yes on input C.
NP-hardness of the unsatisfiability and subsumption tasks can also be demon- strated.
Theorem 2.8.4 ([DLN+92]).
For ALE concept expressions, unsatisfiability and subsumption are both NP-hard. Proof. The original proof in [DLN+92] uses a reduction from the NP-complete problem One-in-three 3SAT, but here we outline another reduction from the exact cover problem which was presented in [Don03]. The exact cover problem (cf. [GJ79]) is the following: given a set U = {u1, ..., un} and a set S = {S1, ..., Sm} of subsets
of U, determine whether there exists an exact cover, that is, a subset {Sj1, ..., Sjq}
of S such that Sjh∩ Sjk = ∅ for h 6= k and
Sq
k=1Sjk = U. We will show that U, S
has an exact cover if and only if the ALE concept CU ,S pictured in Figure 2.5 is unsatisfiable.
CU ,S = D1,1⊓ ... ⊓ D1,m⊓ E where the Di,j are defined inductively as follows
Di,j = (
∃R.Di+1,j,if either i ≤ n, ui∈ Sj, or i > n and ui−n∈ Sj ∀R.Di+1,j,if either i ≤ n, ui6∈ Sj, or i > n and ui−n6∈ Sj for i ∈ {1, ..., 2n} and D2n+1,j = ⊤, and E = ∀R....∀R.
| {z } 2n
⊥.
Figure 2.5: The concept CU ,S which codes an instance U = {u1, ..., un}, S = {S1, ..., Sm} of the exact cover problem.
The first direction (U, S has an exact cover ⇒ CU ,S is unsatisfiable) is rather straightforward, so we concentrate on the second part of the equivalence. Suppose then that the concept CU ,S is unsatisfiable. It follows that |= D1,1⊓ ... ⊓ D1,m ⊑ (∃R)2n⊤. We partition {1, ..., m} into two sets: a first set J∃
1 containing those indices j for which D1,j = ∃R.D2,j, and a set J1∀ containing those indices j for which D1,j = ∀R.D2,j. We next define inductively a sequence of integers h1, ..., h2n and sequences of sets J2∃, ...,J∃
2n and J2∀, ...,J2n∀ in the following manner: - hi is an element of Ji∃ such that |= (⊓j∈J∀
i Di+1,j) ⊓ Di+1,hi ⊑ (∃R)
2n−i⊤ - Ji∃ = {j | j ∈ Ji−1∀ ∪ {hi−1} and Di,j = ∃R.Di+1,j}
- Ji∀ = {j | j ∈ Ji−1∀ ∪ {hi−1} and Di,j = ∀R.Di+1,j}
This definition is well-founded since the initial sets J1∃ and J1∃ have already been defined above. Moreover, the fact that hi is chosen so that |= (⊓j∈J∀
i Di+1,j) ⊓
Di+1,hi ⊑ (∃R)2n−i⊤ guarantees the existence of an element h
i+1 of Ji+1∃ with the required properties. We remark that by construction for every 1 ≤ i ≤ 2n − 1 we have:
(a) Ji+1∃ ∪ Ji+1∀ ⊆ Ji∃∪ Ji∀ (b) |J∃
i ∩ (Ji+1∃ ∪ Ji+1∀ )| = 1
We intend to show that Σ = {Shn+1, ..., Sh2n} is an exact cover for U, S. We first
remark that because of the way that hi are defined, for each 1 ≤ i ≤ n, we have Dn+i,hn+i = ∃R.Dn+i+1,hn+i, which means that each element ui ∈ U belongs to
60 2.8. Relation to Description Logics
some set in Σ (namely the set Shn+i). It remains to be shown that the sets in
Σ are pairwise disjoint. Suppose for a contradiction that some ui appears in two distinct sets Shn+f and Shn+g in Σ. That means that Di,hn+f = ∃R.Di+1,hn+f and
Di,hn+g = ∃R.Di+1,hn+g. We also know that hn+f ∈ J
∃
n+f and hn+g ∈ Jn+g∃ , and hence hn+f ∈ Ji∃ and hn+g ∈ Ji∃ (by (a)). It follows then from (b) that either hn+f 6∈ J∃
i+1∪ Ji+1∀ or hn+g6∈ Ji+1∃ ∪ Ji+1∀ . But then using (a), we find that either hn+f 6∈ J∃
n+f or hn+g6∈ Jn+g∃ , which is a contradiction.
Note that the concept CU ,S used in the reduction in the preceding proof has a very simple syntax (conjunction of strings of role restrictions followed by atomic literals). We will make use of this fact in later chapters.
3
Prime Implicates and
Prime Implicants in
Kn
The purpose of this chapter is to select a suitable definition of prime implicates and prime implicants for the logicKn. The first half of the chapter will be concerned with the generalization of the notions of clauses and terms to Kn. As there is no obvious definition, we will enumerate a list of syntactic, semantic, and complexity-theoretic properties of propositional clauses and terms, which we will then use to compare the different candidate definitions. In the second half of the chapter, we will consider the different definitions of clauses and terms in light of the notions of prime implicate and prime implicant they induce. Once again, we will list some basic properties from the propositional case that we would like to satisfy, and we will see how the different definitions measure up.
3.1
Defining Clauses and Terms in
K
nAs we have seen in Chapter 1, the notions of prime implicates and prime impli- cants are straightforwardly defined using the notions of clauses and terms. Thus, if we aim to provide suitable definitions of prime implicates and prime implicants for Kn, a logical first step is to come up with an appropriate definition of clauses and terms in Kn. Unfortunately, whereas clauses and terms are standard notions in both propositional and first-order logic1, there is no generally accepted definition
1. One might wonder why we don’t simply translate our formulae in Kninto first-order formulae and then put them into clausal form. The reason is simple: we are looking to define clauses and terms within the language of Kn, and the clauses we obtain on passing by first-order logic are
62 3.1. Defining Clauses and Terms in Kn
of clauses and terms in Kn. Indeed, a couple of different notions of clauses and/or terms for Kn have been proposed in the literature for various purposes.
Instead of blindly picking a definition and hoping that it is appropriate, we prefer to list a number of characteristics of literals, clauses, and terms in propositional logic, which will provide us with a principled means of comparing different candidate definitions. Each of the properties below describes something of what it is to be a literal, clause, or term in propositional logic. Although our list cannot be considered exhaustive, we do believe that it covers the principal syntactic, semantic, and complexity-theoretic properties of the propositional definition.
P1 Literals, clauses, and terms are in negation normal form.
P2 Clauses do not contain ∧, terms do not contain ∨, and literals contain neither ∧ nor ∨.
P3 Clauses (resp. terms) are disjunctions (resp. conjunctions) of literals.
P4 The negation of a literal is equivalent to another literal. Negations of clauses (resp. terms) are equivalent to terms (resp. clauses).
P5 Every formula is equivalent to a finite conjunction of clauses. Likewise, every formula is equivalent to a finite disjunction of terms.
P6 The task of deciding whether a given formula is a literal, term, or clause can be accomplished in polynomial-time.
P7 The task of deciding whether a clause (resp. term) entails another clause (resp. term) can be accomplished in polynomial-time.