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Ultimate Well-founded and Stable Semantics for Logic Programs with Aggregates

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Abstract

. In this paper, we propose an extension of the well-founded and stable model semantics for logic programs with aggregates. Our approach uses Approximation Theory, a xpoint theory of stable and wellfounded xpoints of non-monotone operators in a complete lattice. We dene the syntax of logic programs with aggregates and dene the immediate consequence operator of such programs. We investigate the wellfounded and stable semantics generated by Approximation Theory. We show that our approach extends logic programs with stratied aggregation and that it correctly deals with well-known benchmark problems such as the shortest path program and the company control problem. 1
Ultimate Well-founded and Stable Semantics for
Logic Programs with Aggregates
Marc Denecker
a
Nikolay Pelov
b
Maurice Bruynooghe
b
a
Universit´e Libre de Bruxe lles, Bld du Triomphe CP 212, 1050 Brussels, Belgium
b
K.U.Leuven, Celestijnenlaan 200A, 3001 Heverlee, Belgium
In [3] we investigate the problem of defining a well-founded and stable s e -
mantics for programs with aggregates. Our work is based on Approximation The-
ory [1] which is a general algebraic framework for approximating non-monotone
operators on a complete lattice L by approximating operators o n the bi-lattice L
2
.
The theory identifies basic properties of the approximating operators and gives
a method to construct a stable ope rator and their associated fixpoints - Kripke-
Kleene (KK), well-founded (WF), and set of stable fixpoints. The authors then
show that the different fixpoints enjoy similar properties and relationships a s the
corresponding semantics in standard logic programming. For example the WF
fixpoint is mo re precise than the KK fixpoint and a lso approximates every stable
fixpoint. Moreover, stable fixpoints are always minimal fixpoints.
In a mo re recent paper [2] the authors study the concept of precision of an
approximating oper ator. They show that more precise approximating operators
have mo re precise KK and WF fixpoints and a larger number of stable fixpoints.
Moreover, there exists a most-precise approximating operator which they call the
ultimate approximation. In contrast with other approximating op e rators which
have to be defined explicitly, the construction of the ultimate approximating oper-
ator is entirely algebraic and depends only on the original non-monotone oper ator.
This makes it particularly well-suited for our purposes be cause defining a T
P
oper-
ator for programs with aggregates is relatively straightforward. Another advantage
of the ultimate approximation is that in cases where T
P
is monotone the ultimate
well-founded model will be 2-valued and will coincide with the least fixpoint of
T
P
. This is not the case for the standard well-founded semantics. For example in
the standard well-founded model of the pr ogram:
p ¬p.
p p.
p is undefined while the associated T
P
operator is monotone and p is true in the
ultimate well-founded model.
One disadvantage of using the ultimate semantics is that it has a higher com-
putational cost even for programs without aggregates. The complexity goes one
level higher in the polynomial hierarchy to
p
2
for the well-founded model and to
Σ
p
2
for a stable model which is also complete for this cla ss [2]. Fortunately, by
adding aggregates the complexity does not increase further.
To g ive an example of a logic program with aggregates we consider the problem
of computing the length of the shortest path between two nodes in a directed graph.
The graph is represented with a set of edge(X, Y, W ) facts meaning that there is
an edge between X and Y with weight W . The program consists of a single rule:
sp(X, Y, L) min({C | edge(X, Y, C)
Z, C
1
, C
2
. (sp(X, Z, C
1
) edge(Z, Y, C
2
)
C = C
1
+ C
2
)}, L).
This program shows the syntax which we use. First of all, we allow arbitrary
first-order fo rmulas in the bodies of rules and in the conditions of set expressions.
Unlike most o f the previous work o n aggregates, we use an explicit notation for set
expressions {X | ϕ[X]} denoting the set of all elements d for which the condition
ϕ[d] is true. Aggregate functions are written in a form of atoms like f(s, t) where
F is an aggregate function, s is a set expression, and t is a term. It will evaluate
to true if the aggregate function f applied to the set denoted by s is equal to the
interpretation of the term t.
Having defined a 2-valued semantics fo r formulas containing aggregate atoms
it is easy to extend the definition of the 2-valued van Emden-Kowalski immediate
consequence operator T
P
for programs with a ggregates. Constructing the ultimate
approximating operator of T
P
we obtain an ultimate well-founded and ultimate
stable semantics for pro grams with aggregates. The two semantics have all the
properties which we discussed earlier. In addition for aggregate stratified programs
the ultimate well-founded model will be 2-valued and will coincide with the unique
ultimate stable model.
Our current research is focused on defining a less precise a pproximating oper-
ator for programs with aggregates which extends the s tandard well-founded and
stable semantics for programs without aggregates. Although the complexity of
this operator will still be the same as the the complexity of the ultimate approx-
imation, if we limit our language to some specific aggregate functions we can stay
in the complexity classes o f the standard semantics - P for the well-founded model
and NP for the stable models.
References
[1] M. Denecker, V. Marek, and M. Truszczy´nski. Approximating operators, stable
operators, well-founded fixpoints and applications in non-monotonic reasoning.
In J . Minker, editor, Logic-based Artificial Intelligence, pages 127–144. Kluwer
Academic P ublishers, 2000.
[2] M. Denecker, V. Marek, and M. Truszczy´nsky. Ultimate approximations in
nonmonotonic knowledge representation systems. In, KR’02, pages 17 7–188.
Morgan Ka ufmann, 2002.
[3] M. Denecker, N. Pelov, and M. Br uy nooghe. Well-founded and stable model
semantics for logic programs with aggregates. In P. Codognet, editor, ICLP’01,
volume 2237 of LNCS, pages 212–226. Springer-Verlag, 2001.
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