lht[thm]Lyndon Theorem
Key words:
circumscription, closed-world assumption, default assumptions,
domain-closure axiom, unique-names assumption, model theory for non-monotonic
logics, preference relations.
AMS classification: 68G99, 03C40, 03C52.
Given set of premises S, assume j if and only if, for every g Î G, SÈ{j} does not entail g unless S does,where G and S are sets of clauses, and j is a clause. The problem of "-completeness of DAG with respect to finest model semantics is investigated. A method of deriving "-completeness of DAG1 ÇG2 assuming DAG1 and DAG2 are known to be "-complete is presented. This method yields "-completeness of instances of DAG with respect to totally minimal semantics, discriminant minimal semantics, Herbrand semantics, and minimal Herbrand semantics. It is shown that the last of these completeness results is strictly stronger than analogous characterization using an extension of the generalized closed-world assumption GCWA.
In this paper, we investigate instances of the following scheme D of default reasoning:
If the assumption j doesn't introduce unwanted consequences to the set of premises S then assume j.Although scheme D does not seem to cover all the default rules discussed in professional literature, it has a number of intriguing applications in deductive data bases and in logic programming. For example, all published versions of the closed-world assumption are, in fact, instances of this scheme. If the set of ``unwanted consequences", say G, is finite then D may be expressed in the form of a set of Reiter style default rules of inference:
| (1) |
|
Using the default scheme D in the context of reasoning from an arbitrary set of premises of S involves a subtlety. If S itself entails consequences that are unwanted, then the requirement ``j doesn't introduce unwanted consequences" should be understood as ``j doesn't entail any unwanted consequence, unless this unwanted consequence is already entailed in S". This observation, given the set G of all unwanted consequences, leads to the formalization of D by the following postulate:
Assume j if and only if, for every g Î G, SÈ{j} does not entail g unless S does.We will refer to it as the G-default assumption, and denote the set of all j that satisfy the above definition by DAG(S).
The consistency of DAG(S) seems to be a serious problem that is reportedly common to all kinds of default rules. In particular, it may happen that each of a pair j, y of inconsistent sentences separately does not add any unwanted consequences to S, and then both of them are included in DAG(S), making DAG(S) inconsistent. In this paper, we have managed to avoid this problem by restricting both S and DAG(S) to sentences which do not reveal such pathological behavior. Most notably, clauses, or universally quantified sentences, do not cause this type of a problem for appropriately chosen G. As a result of this precaution, the instances of the G-default assumption which are studied here may be treated as rules of inference and used whenever applicable, without contradicting the other uses of the same instance of G-default assumption. This desirable proof-theoretic property frees us from fixed-point equations which seem inevitable for the default rules that do not possess this feature.
Consistency of DAG(S) creates the possibility of
characterizing it in terms of its models, which is an object of
our primary concern.
A question which we will attempt to address to the fullest extent possible
is:
Given G, what semantics assigns to every S from the domain of DAG the class of first-order models of DAG(S)?We will seek candidates for such semantics among models of S which are finest with respect to certain preference relations (called refinements in this paper) that are characteristic for certain instances of G. This approach leads to a number of completeness results of the form:
j Î DAG(S) if and only if every finest model of S is a model of j.The instances of G we investigate in this paper are the sets of clauses positive beyond equality, clauses positive in equality, ground clauses, the intersections of these sets, and the set of clauses negative in equality. The corresponding minimal semantics are: predicate-minimal semantics, discriminant semantics, domain-minimal semantics, and their combinations. For example, if G consists of all positive ground clauses then DAG is "-complete with respect to minimal Herbrand (i.e., predicate-minimal, domain-minimal, and discriminant) semantics; a result whose extreme instances (e.g., no = in the language) were known for some time in a weaker form. It is our hope that our uniform analysis of these cases will clarify the actual relationships between different patterns of model minimization described in the literature.
We apply the standard terminology and notation of first-order model theory, a good account of which can be found in [], Chap. A2. We restrict ourselves to a first-order language L with logical connectives Ù (and ), Ú (or ), Ø (not ), " (for all ) and $ (there exists), and treat all other connectives as abbreviations. In addition to predicates, L contains constants and the equality symbol =1, and may contain function symbols. We identify L with the set of its all formulas. To avoid confusion with connectives of L, we apply beyond L the informal quantifiers Ù and Ú as abbreviations for for all and there exists. For instance,
|
For every formula j of L, "x j is a formula of L.
A formula j is atomic if and only if no logical connective
appears in j. For example, x = f(d) is an atomic formula. A
"-formula is a formula of the form "x1 "x2 ..."xn j (abbreviated as "[
] j), where
j is quantifier-free. Similarly, an $-formula is a formula of
the form $x1 $x2 ... $xn j (abbreviated
as $[
] j), where j is quantifier-free. A
sentence is a formula without free (i.e., unquantified) variables.
Atom denotes the set of all atomic sentences of L; QF denotes the set
of all quantifier-free sentences of L; and " and $, when
used in appropriate context, denote the set of all "-sentences and
the set of all $-sentences of L, respectively.
"-sentences seem to play a very important role in artificial intelligence. In particular, every clause is logically equivalent to a "-sentence. Also, every "-sentence is logically equivalent to a finite set of clauses. Therefore, in this paper "-sentences are given special attention. Moreover, we identify sets of clauses with subsets of ", and sets of ground clauses with subsets of QF. Obviously, this can be done without loss of generality.
SL denotes the class of all first-order structures for L.
We usually denote its elements by A, B, M, N, ..., and their respective domains by A, B, M, N, ...,. If
F is a function symbol of L then FM denotes the corresponding
function in M. Analogously, RM denotes the relation in
M corresponding to the predicate R. The satisfaction
relation is denoted by
,
so that M
j[s]
means that formula
j is satisfied in structure M by assignment s on
its free variables (formally, s is a function from variables of L into the
domain M of M). If j is satisfied in M by every
assignment s then M
j is used instead of
M
j[s].
In such a case we say that j is true in M.
If j is a sentence of L then
for every assignment s in M, M
j[s]
is synonymous with M
j.
We use M Í N,
to mean that M is a substructure of N,
if and only if
M Í N, and for every
predicate or function symbol F of L, FM = FN | \` M,
where `` | \` "
means ``restricted to".
A theory S in L is a set of sentences of L.
Here we usually denote
formulas by lower-case Greek letters, and theories by upper-case Greek letters.
We write M
S to express that for every j Î S, M
j.
M
S means that all elements of S are true in
M, that is,
the structure M is a model of S. We denote the class of all models of S by
Mod(S). We make an implicit use of the completeness theorem of
first-order logic by applying S
j in the sense
Mod(S) Í Mod(j),
so that S
j means that
j is true in every model of S.
If f is a function from subclasses of SL into
subclasses of SL then
f is a relation defined by:
| (2) |
We use Cn(S) to denote the set { j | S
j} of all first-order consequences of S
within the language L.
We say that S1 is logically equivalent to S2 if and
only if Cn(S1) = Cn(S2), or equivalently, if and only if
Mod(S1) = Mod(S2).
Moreover
if G is a set of sentences of L then we use
SG to denote the set
Cn(S) ÇG. In particular, SL coincides with
Cn(S).
The notion of relative positiveness and negativeness are
the key concepts which allow for
proper articulation of default assumptions that are
"-complete with respect to various versions of minimal semantics.
Let  be a set of predicates of L. Our intention is that  contains all predicates which are being minimized, while the predicates not in  remain constant. A formula is positive in a symbol R if and only if it does not contain an appearance of R in a scope of a negation2. It is positive if and only if it is positive in every predicate in  and in the equality symbol =. A formula is negative in R if and only if it is a negation of a formula which is positive in R. In this paper, Pos { = } ¢ denotes the set of all "-sentences which are positive in all predicates in  (symbol ``¢" in Pos { = } ¢ indicates that = is excluded from the requirement of positiveness), Pos { = } denotes the set of all "-sentences which are positive in =, Pos (the intersection of Pos { = } ¢ and Pos { = } ) denotes the set of all positive "-sentences, and Neg { = } denotes the set of all "-sentences which are negative in =. Let us note that elements of Pos may contain negative occurrences of predicates from beyond Â.
A
conservative homomorphism on M into N is a mapping f : M® N such that for each atomic formula j without
an occurrence
of the
symbol =, and assignment s in M,
|
|
If µ is a binary relation on a class S then a subclass K of
S is called upward µ -closed if and only if
M Î K and M µ N imply
N Î K. The upward µ -closure
Clo µ (K) of K is defined as the least
upward µ -closed class containing K as a subset. If µ is
a reflexive and transitive relation then
| (3) |
| (4) |
Transitive and reflexive closure of a relation µ is denoted by µ *. If µ 1 and µ 2 are binary relations on S then µ 1 ° µ 2 denotes their composition, and µ 1 + µ 2 denotes their combination, that is, the relation ( µ 1 È µ 2)*. If µ 1 and µ 2 are reflexive and transitive then µ 1 + µ 2 = ( µ 1 ° µ 2)*. Let us note that µ 1 ° µ 2 is not necessarily a transitive relation, even though µ 1 and µ 2 are. However, if µ 1, µ 2 and µ 1 ° µ 2 are reflexive and transitive then µ 1 + µ 2 = µ 1 ° µ 2; the converse is true as well. We call µ a partial order if, in addition to being reflexive and transitive, it is antisymmetric, that is, it satisfies the following postulate:
| (5) |
It turns out that appropriately chosen preference relations, which we call here refinements, constitute semantical counterpart of G-default assumption. The purpose of a refinement is to modify a model M of a set of sentences S to another model N of S, which satisfies more consequences of an instance of G-default assumption in question and, in effect, better approximates the reality that S under this default assumption is supposed to describe. Consequently, the mostly preferred models of S which cannot be further refined will provide DAG(S) with adequate semantics. In Sections and we will determine which refinements are appropriate matches for selected instances of the G-default assumption. Here, we define refinements as binary relations between first-order structures of SL, and state their basic properties.
A refinement, usually
denoted by µ (possibly with subscripts), is a partial
order on the class SL of first-order structures for L.
N µ M expresses the fact that N is a
refinement of M.
Given K Í SL, the class fin µ (K) of
µ -finest structures in K is defined by
| (6) |
The entailment
is incomplete
with respect to the µ -finest semantics. Indeed, a sentence
j that is
not provable from S by means of
, or in other words,
is false in some elements of Mod (S), may be true in all
elements of fin µ (Mod (S)).
This fact motivates our interest in
the entailment
fin µ , denoted for simplicity by
µ ,
which by definition (2) is complete with respect to the
µ -finest
semantics. Since fin µ (K) always is a subset of K,
µ
is characterized by the following instance of (2):
| (7) |
A subclass K of SL is called µ -flat if and only
if,
| (8) |
We focus on the following instances of the refinement µ . It is a
matter of routine inspection to check that all these instances are
partial orders.
(M £ N) if and only if (M = N, and for every function symbol F of L, FM = FN, and for every predicate symbol P not in Â, PM = PN, and for every predicate symbol R in Â, RM Í RN).Numerous variants of £ -finest semantics turned out to be particularly useful in deductive data bases, logic programming, and other areas of artificial intelligence. One of the applications of this semantics is the definition of the transitive closure TCR of a binary relation R. Although TCR is generally not first-order definable, the following sentence defines TCR in its £ -finest models: ("x)("y)(R(x,y) É TCR(x,y)) Ù("x)("y)("z)((TCR (x,y) ÙTCR (y,z)) É R¢(x,z)), where the only predicate minimized by £ is TCR. Consequently, using minimization one can define relational semantics of programs.
Following generally accepted convention, we call £ -finest models
predicate-minimal models.
The very relation Í between first-order structures comprises our second instance of refinement. It formalizes the Ockham's razor principle in this sense, that the domains of Í -finest structures consist only of necessary individua, namely of interpretations of constant3 terms of the language L. We call Í -finest structures domain-minimal structures. Not every consistent set of sentences has a model being a domain-minimal structure. For example, { $xP(x) } È{ ØP(t) | t is a constant term of L } has not. However, for every theory S Í ", each domain-minimal substructure of a model of S is a model of S.
Domain-minimal structures are also known under the name domain-closed
structures.
MN iff there exists a conservative homomorphism f such that M = fN.
The nature of the refinement
lies in gluing together certain
elements of the domain of a model if they satisfy the same
atomic and negated atomic sentences
of L. Therefore,
may be used to minimize the domains of first-order
structures, albeit, in a different sense than Í .
For instance, in a language with one unary predicate P and three constants
a, b, and c, each
-finest model of
{ P(a), ØP(b), ØP(c) } has the domain consisting of two elements:
one to interpret a and another to interpret b and c.
Oddly enough, something quite converse to gluing
,
namely discrimination,
seems to be a matter of interest in
deductive databases and logic programming.
Discrimination may be defined as the inverse of gluing
restricted to elements of the domain which are values of
the constant terms of L.
We denote the relation of discrimination by
. M
N means that there is a conservative homomorphism f of
M onto N, such that f(m1) = f(m2)
holds only if, for some
constant terms t1 and t2 of L, m1 = t1M, and
m2 = t2M. In particular,
| (9) |
The restriction to strongly discriminant semantics is necessary for
the validity of many published
completeness proofs of negation-as-failure and similar procedures. This
is most likely the reason of popularity of discriminant models.
Of course, if S contains occurrences of the equality symbol, for
instance, a sentence a = b, there may be no strongly
discriminant models of S.
However, we will show in subsection that
for every consistent S Í ", there
are always discriminant models of S, which are strongly discriminant if
= does not occur in S.
It turns out that the most interesting in applications are certain combinations
of the above instances of µ . For example, the combination of
Í and
leads to the concept of the
Herbrand (i.e., domain-minimal and discriminant)
structure, or, in the extreme case to strongly Herbrand
(i.e., domain-minimal and strongly discriminant) structure.
The combination of the three refinements:
Í ,
, and £ yields in the extreme case the concept of
a
minimal strongly Herbrand structure. This notion plays a fundamental
role in model
theory for deductive databases and logic programming.
Combinations of refinements are the central point of our interest. They are the
subject of systematic study in Section .
If certain theories have models which cannot be refined to µ -finest
models than the entailment
µ may reveal an irregular
behavior. In particular, if a consistent theory S has no
µ -finest models at all
(e.g., in the language with a unary predicate symbol N, the usual inductive
definition of natural numbers with the postulate ``N(0)" being replaced by
``$x N(x)", has no predicate-minimal models)
then S entails false, which is decidedly
an unwanted consequence. This troubled situation cannot happen if every
S Í " is µ -densly founded, that is, if
class fin µ (Mod (S)) is µ -dense in Mod (S). Fortunately,
this
is the case for all the refinements considered in this paper.
Lemma 1
For every S Í ",
Proof.
(3.6) was proven in [].
(3.6).
Because every first-order structure contains a domain-minimal
structure as a substructure, the density of fin Í (Mod(S)) in Mod(S) is secured by the o\'s-Tarski
Theorem (see [], thm 3.11).
(3.6) was proven in [], lem. 7.4.
(3.6).
Let K = { N
(Mod (S)) is
-dense in Mod (S).
(Mod (S)) is
-dense in Mod (S).
A | N
S},
and let A1
...
Ai
... , i Î I,
be a chain in K. Let E(M) denote the set of all equational
atomic sentences of L satisfied by M. There exists B Î SL, with B
A and
E(B) = Çi Î I E(Ai). Of course,
B
Ai for each i Î I. Let fi be a
conservative homomorphism from B onto Ai.
An inductive argument
shows that for every quantifier-free formula j of L, and
every assignment s in B,
(the case of atomic and negated atomic equational formula follows from the
definition of B,
the case of atomic and negated atomic predicate formula
follows from the conservativeness of fj, the cases of j1 Új2 and j1 Ùj2 are routine).
From this we conclude, by induction again,
Ú
i Î I
Ù
j, k Î I : j, k > i
Aj
j[s °fj] iff Ak
j[s °fk]
Hence, for every
sentence j Î ",
B
j[s] iff
Ú
i Î I
Ù
j Î I : i < j
Aj
j[s °fj]
Since Ùi Î I Ai
B
j iff
Ú
i Î I
Ù
j Î I : i < j
Aj
j.
S, we conclude
B
S. By the
Kuratowski - Zorn Lemma (cf. [], thm
4.1), K contains a minimal (with respect to
) element M.
Obviously, M
A and M Î fin
(Mod(S)). Hence (3.6).
[¯]
Let G be a set of "-sentences of L. The G-default assumption DAG introduced in Section 1 is formally defined as a consequence operation from subsets of " into subsets of ", given by:
| (10) |
It turns out that those
G's, whose elements' truthfulness is upward
µ -preserved, yield instances of
G-default assumption which
are "-complete with respect to
the refined entailments
µ .
Definition 1
We call a set G of sentences of L a complete preservation
property with respect to the refinement µ , in abbreviation:
CPP(G, a), if and only if,
[¯]
Ù
S Í "
Mod(SG) = Clo µ (Mod (S)). (11)
| (12) |
The notion of
complete preservation property constitutes a fundamental concept which
allows us to establish the
"-completeness of
the G-default assumption with respect to refined entailment
µ .
The Completeness Theorem 2
Assume that CPP(G, µ ) holds.
For every µ -densly founded
S Í " and j Î ",
Proof.
We show that under these assumptions,
S
S
µ j iff j Î DAG ( S).
µ j if and only if
(SÈ{ j})G = SG. Indeed,
S
µ j iff [by definition
(7)
of
µ ]
fin µ (Mod (S)) Í Mod(j) iff
Mod(j) is µ -dense in
fin µ (Mod (S)) iff [by µ -densly foundedness
of S, that is by
µ -density of
fin µ (Mod(S))
in Mod(S)]
Mod(j) is µ -dense in Mod(S)
iff [by (3) and reflexiveness and transitivity of µ ]
Mod(S) Í Clo µ (Mod(S) ÇMod(j)) iff
Mod(S) Í Clo µ (Mod(SÈ{ j} )) iff [by CPP(G, µ ) and
(11)]
Mod(S) Í Mod((SÈ{ j} )G). Observation that
SG Í (SÈ{ j})G
always holds completes the proof.
[¯]
Lemma 3
The following complete preservation properties hold:
Proof.
(4)
We have to demonstrate that
(4)
We have to demonstrate that
(Þ)
Let A
(4)
We have to demonstrate that
(4)
Obviously, Clo
[¯]
Because £ is a transitive and reflexive relation, it suffices to show that
for every S Í " and every A Î SL,
Ù
S Í "
Mod(SPos { = } ¢) = Clo £ (Mod (S)).
This has been done in [], cor. 3.6.
A
SPos { = } ¢ iff
Ú
M £ A
M
S.
Because Í is a transitive relation, it suffices to show
that
for every S Í " and every A Î SL,
Ù
S Í "
Mod(SQF) = Clo Í (Mod (S)).
(Ü)
Assume A
A
SQF iff
Ú
M Í A
M
S. ![]()
SQF. Take any j Î SQF with A ![]()
j, that is,
A
Øj, and any M Í A.
Of course,
M
Øj, that is,
M ![]()
SQF.
SQF and let B be a domain-minimal
substructure of A. We show that B
S.
Suppose not, that is, let j Î S be such that
B ![]()
j. Because S Í ", j
has the form of "[
] y([
]),
where y([
]) is quantifier-free. We have
B
$[
] Øy([
]). Since B is a
domain-minimal structure, there exists a sequence [
] of constant terms of L
with B
Øy([
]). Because B Í A, we obtain A
Øy([
]). On the other hand,
y([
]) Î SQF , therefore
A
y([
]), a contradiction.
Because
Ù
S Í "
Mod(SNeg { = } ) = Clo
(Mod (S)).
is a
transitive and reflexive relation, it suffices to show that
for every S Í " and every A Î SL,
This has been done in [], cor. 7.2.
A
SNeg { = } iff
Ú
M
A
M
S.
(Mod(S)) Í Clo
(Mod(S)).
Clo
(Mod(S)) Í
[by (9)]
Clo
( Clo Í (Mod(S))) =
Clo
(Mod(S)).
The proof of
is symmetric to (4).
Hence, (4).
Ù
S Í "
Mod(SPos { = } ) = Clo
(Mod (S))
Theorem 4
For every S Í " and every j Î ",
Proof by application of Lemmas 3.6 and 4,
and Theorem 4
[¯]
£ j iff j Î DAPos { = } ¢ ( S)
Í j iff j Î DAQF ( S) ![]()
j iff j Î DANeg { = } ( S) ![]()
j iff j Î DAPos { = } ( S)
DAPos { = }¢ was first introduced
as an instance of operation
cwaS, and
proven complete with respect to entailment
£
in [].
In this section, we investigate combinations of refinements. We prove that the resulting "-complete default assumptions are straightforward combinations of the simple ones.
We start with technical lemmas
(Lemmas - ) which yield a handy tool for
surgically clean analysis of the following
combinations of instances of µ that were introduced in Sections
3 and 4:
Lemma 1
Assume that µ 1 ° µ 2 is transitive. Then for every
K Í SL,
Proof. It suffices to show that
Clo µ 2(Clo µ 1(K))
is upward µ 1-closed. Let
M Î Clo µ 2(Clo µ 1(K)), and M µ 1 N. By the reflexiveness of
µ 2 we get M µ 1 ° µ 2 N.
By (3) we obtain
ÚA,B Î KA µ 1 B µ 2 M, that is,
ÚA Î KA µ 1 ° µ 2 M.
The transitivity of µ 1 ° µ 2 yields
ÚA Î KA µ 1 ° µ 2 N, that is, by (3)
again,
N Î Clo µ 2(Clo µ 1(K)). Thus
Clo µ 2(Clo µ 1(K)) is upward µ 1-closed.
[¯]
Clo µ 2(Clo µ 1(K)) = Clo µ 1(Clo µ 2(Clo µ 1(K))) . (13)
The following lemma is interesting in its own right since it
generalizes classic results
of Craig [] and Lyndon [].
Interpolation Lemma 2
Assume that
CPP(G1 , µ 1) and CPP(G2 , µ 2)
hold,
µ 1 ° µ 2 is a partial order,
and G1 and G2 posses the
intersection property.
Then
Proof. SG1 ÇG2 = Cn(S) ÇG1ÇG2 Í Cn(Cn(S) ÇG1) ÇG2 = (SG1)G2. Hence,
Mod((SG1)G2) Í Mod(SG1 ÇG2).
Therefore, it suffices to prove that
Mod(SG1 ÇG2) Í Mod((SG1)G2).
Indeed,
Mod((SG1)G2) =
[by CPP(G2, µ 2) and (3)]
Clo µ 2(Mod(SG1)) =
[by
CPP(G1, µ 1) and (3)]
Clo µ 2(Clo µ 1(Mod(S))) =
[by Lemma 5]
Clo µ 1(Clo µ 2(Clo µ 1(Mod(S)))) = [by similar argument]
Mod(((SG1)G2)G1).
Because ((SG1)G2)G1 Í G1 and (SG1)G2 Í G1,
the intersection property of G1 and G2 yields
P Í G1 ÇG2 with
Mod((SG1)G2) =
Mod(P). Since
Mod(S) Í Mod((SG1)G2),
we have
Mod(S) Í Mod(P), therefore
P Í SG1 ÇG2.
Hence, Mod(SG1 ÇG2) Í Mod(P). Thus
Mod(SG1 ÇG2) Í Mod((SG1)G2).
[¯]
Ù
S Í "
Mod(SG1 ÇG2) = Mod((SG1)G2). (14)
|
Now, we prove that CPP is preserved under combinations of refinements.
Lemma 3
Assume that CPP(G1 , µ 1) and CPP(G2 , µ 2)
hold, µ 1 ° µ 2 is a partial order,
and G1 and G2 have the
intersection property.
Then CPP(G1 ÇG2, µ 1 + µ 2) holds.
Proof. We must prove that
By Lemma 5,
Mod(SG1 ÇG2) =
Mod((SG1)G2). Therefore, A
Because
µ 1 + µ 2 is reflexive and
transitive, it suffices to demonstrate
that
for every S Í " and A Î SL,
Ù
S Í "
Mod(SG1 ÇG2) = Clo µ 1 + µ 2(Mod(S)). (15)
A
SG1 ÇG2 iff
Ú
M µ 1 + µ 2 A
M
S. (16)
SG1 ÇG2 iff A
(SG1)G2 iff
[because of CPP(G1, µ 1,
CPP(G2, µ 2, and (3)]
A Î Clo µ 2(Clo µ 1(Mod(S))) iff
[because of reflexiveness and transitivity of µ 2]
ÚN µ 2 A N Î Clo µ 1(Mod(S)) iff
[because of transitivity of µ 1]
ÚN µ 2 A ÚM µ 1 N M
S iff
ÚM µ 1 ° µ 2 AM
S
iff
[because of transitivity of µ 1 ° µ 2,
µ 1 + µ 2 = µ 1 ° µ 2]
ÚM µ 1 + µ 2 A M
S. Hence (16).
[¯]
Lemma 4
For every upward µ 1 + µ 2-closed class
K Í SL,
( Ê ) Assume M Î fin µ 1 (K) Çfin µ 2 (K). Let N Î K satisfy
N µ 1 + µ 2 M, with N ¹ M.
There is A Î SL, A ¹ M, with
N µ 1 + µ 2 A µ i M,
where i Î { 1 , 2 }. By upward µ 1 + µ 2-closedness
of K,
A Î K. Hence,
M
For every K Í SL,
( Ê )
Assume M Î fin µ (Clo µ (K))
and N Î K, with
N µ M. In particular,
N Î Clo µ (K), therefore
µ -finestness of M yields N = M. Hence,
M Î K, and
M Î fin µ (K).
[¯]
For every K Í SL,
fin µ (K) is µ -dense in K iff
fin µ (K) is µ -dense in
Clo µ (K).
Proof follows from
fin µ (K) Í K
Í Clo µ (K) and
µ -density of K in
Clo µ (K).
[¯]
For every K Ì SL,
fin µ (K) is µ -dense in K iff
fin µ (Clo µ (K)) is µ -dense in
Clo µ (K).
Proof by direct application of Lemmas
5 and 5.
[¯]
Proof. The case of ( Í ) follows from
fin µ (K) Í K.
fin µ 1 + µ 2 (K) = fin µ 1 (K) Çfin µ 2 (K). (17)
Î fin µ i (K), a contradiction.
[¯]
Proof. ( Í )
Assume M Î fin µ (K) and
N Î Clo µ (K), with
N µ M. There is A Î K with
A µ N. The transitivity of M yields
A µ M. µ -finestness of M gives
A = M. Therefore, both
N µ M and M µ N hold.
Because µ is a partial order, (5) yields
N = M. Hence,
M Î fin µ (Clo µ (K)).
fin µ (K) = fin µ (Clo µ (K)). (18)
| (19) |
|
Lemma 8
Assume that µ 2 is antipreserving for µ 1,
µ 1 ° µ 2 is a partial order,
fin µ 1(K) is µ 1-dense in K, and
fin µ 2(K) is µ 2-dense in K.
Then
fin µ 1 + µ 2(K) is
µ 1 + µ 2-dense in K.
Proof. By Lemma 5, we may assume
that K is upward µ 1 + µ 2-closed. Therefore,
by Lemma 5, it suffices to show that
Let M Î K,
A Î fin µ 2(K) with
A µ 2 M
[it exists since fin µ 2(K) is µ 2-dense
in K],
B Î fin µ 1(K) with
B µ 1 A
[it exists because fin µ 1(K) is µ 1-dense
in K],
and N Î K with N µ 2 B.
Because µ 1 + µ 2 = µ 1 ° µ 2,
N µ 2 B µ 1 A
yields C Î SL, with
N µ 1 C µ 2 A. Since K is
upward µ 1-closed and N Î K, we see that
C Î K. Therefore, by
A Î fin µ 2(K), (6) yields
C = A. Hence, N µ 1 A.
Since N µ 2 B µ 1 A holds
and µ 2 is antipreserving for µ 1, (19) gives
N = B. Hence,
B Î fin µ 2(K), that is,
B Î fin µ 1(K) Çfin µ 2(K), which gives (20).
[¯]
fin µ 1 (K) Çfin µ 2 (K) is µ 1 + µ 2 -dense in K. (20)
Figure 1
A counterexample.
After all this, the proof of the following fundamental result becomes an
easy exercise.
The Completeness Theorem 9
Assume that CPP(G1 , µ 1) and
CPP(G2 , µ 2)
hold, µ 1 ° µ 2 is a partial order,
µ 2 is antipreserving for µ 1,
and G1 and G2 have the
intersection property.
Then for every µ 1- and µ 2-densly founded
S Í " and for every
j Î ",
Proof.
Lemma 5 yields CPP(G1 ÇG2, µ 1 + µ 2). Lemma 5 gives
µ 1 + µ 2-densly foundedness of every
µ 1- and µ 2-densly founded
S Í ".
Application of Theorem 4 completes the proof.
[¯]
S
µ 1 + µ 2 j iff j Î DAG1 ÇG2 ( S) . (21)
|
Let W be the set of all seven intersections of sets
| (22) |
Lemma 10
Every pair of elements of the set W has the intersection property.
Proof.
We prove that
Pos{ = }¢ and QF have the intersection property.
(The cases of
Pos{ = } and QF, and
Pos{ = }¢ and Pos{ = }
have similar proofs;
the cases involving their intersections are straightforward).
Let S Í QF be logically equivalent to a subset of
Pos{ = }¢.
We may assume without loss of generality that all
elements of S are minimal disjunctions of atomic and negated atomic
sentences. It follows from CPP(Pos{ = }¢, £ ) that £ preserves the
truthfulness of elements of S. Therefore, by the
minimality of its elements,
S does not contain occurrences of predicates from  in a scope of
negation, that is,
S Í Pos{ = }¢.
Therefore, S Í Pos{ = }¢ ÇQF.
[¯]
Main Theorem 11
For every S Í ", and every j Î ",
S
S
S
Proof
by direct application of Lemmas 4, 3.6,
5, and Theorem 5.
[¯]
£ + Í j iff
j Î DAPos{ = }¢ ÇQF ( S)
£ +
j iff
j Î DAPos ( S)
Í +
j iff
j Î DAPos{ = } ÇQF ( S)
£ + Í +
j iff
j Î DAPos ÇQF ( S)
We end this section with a brief account of some more important consequences of Theorem 5.
What if L does not include the equality symbol? Since the class of strongly Herbrand models, or its subclass, has been widely accepted as the standard semantics for deductive data bases and logic programs, exclusion of = from L was perhaps the simplest way to ensure that a consistent set of clauses has a strongly Herbrand model. In this Section, we use the results of Section 5 to determine how the lack of the equality symbol in L affects the the "-completeness of the G-default assumption.
First, let us note that if M is a structure for language L with the equality symbol = then M is also a structure for language L¢ being a result of removal of = from L. Because the satisfaction relation does not depend on whether the sentence in question is embedded in L or L¢, it follows that for every set of sentences S Í L¢, the class of models of S is the same as if S was understood as a set of sentences of L. Of course, the set CnL¢(S) of consequences of S in L¢ is a proper subset of the set CnL(S) of consequences of S in L. Nevertheless, a sentence j Î L¢ is a consequence of S within L¢ if and only if it is a consequence of S in L. Therefore, we have the following fact.
Fact 1
For every S Í L¢,
[¯]
CnL¢(S) = CnL(S) ÇL¢.
µ j
holds
independently of whether one embeds S and j in L or in L¢.
We state this observation in the following form.
Fact 2
For every refinement µ and every S Í L¢,
[¯]
{j Î L¢| S
µ j} = {j Î L|S
µ j} ÇL¢.
Example 3
Let S = {P(c) ÚP(d)}, j = ØP(c) ÚØP(d),
and G = Pos{ = }¢. We have (SÈ{j})GÇL¢ = SGÇL¢, but because Ø(c = d) Î (SÈ{j})G \SG, (SÈ{j})G ¹ SG.
[¯]
Lemma 4
For each S Í "ÇL¢ and
j Î Pos { = } ,
Operation ¢ on
"-formulas of L and sets of "-formulas of L is defined by
induction as follows.
For each strongly discriminant structure M for L, and each
j Î QF,
Proof by routine induction, using Definition 6,
6 - 6.
[¯]
For every S Í "ÇL¢ and j Î QF,
Proof.
Assume j Î G. We are going to show that
S
Case 1: j Î G¢, is obvious since
[by Definition 6.6]
j = j¢ in this case.
Case 2: j Î Pos { = } ÇQF.
S
Case 3: j Î Pos { = } \QF.
Let j = "[
Proof. S
S ![]()
j iff S
j. ![]()
j iff [by Theorem
4.4]
(SÈ{ j} )Pos { = } = SPos { = } iff
[since j Î (SÈ{ j} )Pos { = } ]
j Î SPos { = } iff S
j.
[¯]
( t = t )¢ = true
( t = s )¢ = false
j¢ = j
(Øj) ¢ = Øj¢
(jÙy) ¢ = j¢Ùy¢
("
®
x
j)¢ = "
®
x
j¢
[¯]
G¢ = { j¢ | j Î G} .
M
j iff M
j¢.
Proof.
S
S ![]()
j iff S![]()
j¢.![]()
j iff
[because S does not contain occurrences of =]
j is true in all strongly discriminant models of S
iff [by Lemma 6]
j¢ is true in all strongly discriminant models of S
iff
S![]()
j¢.
[¯]
SG = PG iff SG¢ = PG¢ . (23)
j iff S
j¢, and
P
j iff P
j¢. This will prove
(23).
j iff [by Lemma 6]
S![]()
j iff [by Lemma 6]
S![]()
j¢ iff [by Lemma 6;
note that by Definition 6,
j¢ Î Pos { = } ]
S
j¢.
Similarly, P
j iff P
j¢.
] y([
]), where y([
]) is
quantifier-free.
S
"[
] y([
])
iff
S
y([c
]),
where [c
] is a sequence of constants not in S with [
] and [c
] having the same pattern of repetitions,
iff [using the same argument as in Case 2]
S
y([c
])¢ iff
S
"[
] y([
])¢ iff
[by Definition 6.6]
S
("[
] y([
]))¢.
Similarly, P
j iff P
j¢.
[¯].
µ .
Theorem 9
For every S Í "ÇL¢ and every j Î "ÇL¢,
Proof.
Let us note that the assumption
G Í G¢ÈPos { = } is met for these instances of
G: Pos, QF ÇPos { = } ,
and Pos ÇQF.
Respective instances of G¢ are:
Pos ÇL¢, QF ÇL¢, and Pos ÇQF ÇL¢.
The rest of proof is a
direct application of Lemma 6 to theorem
5.
[¯]
£ +
in
[].
As noted at the end of Section 5,
QF in Theorem 6 may be
replaced with the set of ground clauses, Pos with the set of
clauses positive in every symbol in Â,
and Pos ÇQF with the set of ground clauses positive
in every symbol in Â.
We conclude this Section with the application of Theorem 6 to
the evaluation of
the degree of completeness of
published in []
extended version GCWA* of
Minker's GCWA.
Let us note that the condition involved in the
definition of G-default assumption, namely
| (24) |
| (25) |
| (26) |
One should note, however, that although for some refinements
µ that do not
involve Í (and consequently,
respective µ -finest semantics
are not restricted to domain-minimal
semantics), their complete preservation properties G satisfy
|
Example 10
Put S = {P(a) ÚQ(b)}.
One can check that GCWA*(S)
ØP(c) . On the other hand,
"x ØP(x) is inconsistent with S.
Hence, j(c)
cannot be used as a valid replacement for
("x)(j(x)) when GCWA* is used.
Consequently,
GCWA* (S) ![]()
("x)(ØP(x) ÚØQ(x)),
even though
S
£ + Í +
("x)(ØP(x) ÚØQ(x)). Of course, by Theorem 6.6,
("x)(ØP(x) ÚØQ(x)) Î DAPos ÇQF ÇL¢ (S).
[¯]
Default rules of inference were introduced by Reiter in [], also the inventor of the closed-world assumption ([]), and quickly became a very fashionable subject of research. At the same time, McCarthy in his famous paper [] about circumscription initiated investigations of first-order minimal models. Second-order variant of circumscription was proven complete with respect to minimal-model semantics by Lifschitz in []. A restricted form of scheme (25) was first used by Minker in [], with subsequent ground-complete extensions by Yahya and Henschen ([]), and Gelfond, Przymusi\'nska and Przymusi\'nski ([]). Credit for the first proof of dense foundedness is due to Bossu and Siegel ([]).
Marczewski in [] and Lyndon in [] (followed by
[]) were first to study preservations of positive sentences. The
consequence operation defined by
| (27) |
I would like to thank Klaus Kaiser for his kind invitation to write this paper, Barbara Tillman for her patience when I ruined our vacation plans, Ehren Evans and Henrietta Okeke for turning the hieroglyphic manuscript into a neat LATEX document, Ken Ganezer for his improvements of my ESL, and Anonymous Referee for his favorable comments and helpful suggestions.
1The case of L without = is addressed in Section .
2The concept of positiveness is purely syntactic, so that a non-positive formula may be logically equivalent to a positive one; similarly, a non-atomic formula may be logically equivalent to an atomic formula.
3i.e., with no occurrences of variables