1,022 research outputs found
The DLV System for Knowledge Representation and Reasoning
This paper presents the DLV system, which is widely considered the
state-of-the-art implementation of disjunctive logic programming, and addresses
several aspects. As for problem solving, we provide a formal definition of its
kernel language, function-free disjunctive logic programs (also known as
disjunctive datalog), extended by weak constraints, which are a powerful tool
to express optimization problems. We then illustrate the usage of DLV as a tool
for knowledge representation and reasoning, describing a new declarative
programming methodology which allows one to encode complex problems (up to
-complete problems) in a declarative fashion. On the foundational
side, we provide a detailed analysis of the computational complexity of the
language of DLV, and by deriving new complexity results we chart a complete
picture of the complexity of this language and important fragments thereof.
Furthermore, we illustrate the general architecture of the DLV system which
has been influenced by these results. As for applications, we overview
application front-ends which have been developed on top of DLV to solve
specific knowledge representation tasks, and we briefly describe the main
international projects investigating the potential of the system for industrial
exploitation. Finally, we report about thorough experimentation and
benchmarking, which has been carried out to assess the efficiency of the
system. The experimental results confirm the solidity of DLV and highlight its
potential for emerging application areas like knowledge management and
information integration.Comment: 56 pages, 9 figures, 6 table
Eliminating Recursion from Monadic Datalog Programs on Trees
We study the problem of eliminating recursion from monadic datalog programs
on trees with an infinite set of labels. We show that the boundedness problem,
i.e., determining whether a datalog program is equivalent to some nonrecursive
one is undecidable but the decidability is regained if the descendant relation
is disallowed. Under similar restrictions we obtain decidability of the problem
of equivalence to a given nonrecursive program. We investigate the connection
between these two problems in more detail
Queries with Guarded Negation (full version)
A well-established and fundamental insight in database theory is that
negation (also known as complementation) tends to make queries difficult to
process and difficult to reason about. Many basic problems are decidable and
admit practical algorithms in the case of unions of conjunctive queries, but
become difficult or even undecidable when queries are allowed to contain
negation. Inspired by recent results in finite model theory, we consider a
restricted form of negation, guarded negation. We introduce a fragment of SQL,
called GN-SQL, as well as a fragment of Datalog with stratified negation,
called GN-Datalog, that allow only guarded negation, and we show that these
query languages are computationally well behaved, in terms of testing query
containment, query evaluation, open-world query answering, and boundedness.
GN-SQL and GN-Datalog subsume a number of well known query languages and
constraint languages, such as unions of conjunctive queries, monadic Datalog,
and frontier-guarded tgds. In addition, an analysis of standard benchmark
workloads shows that most usage of negation in SQL in practice is guarded
negation
Magic Sets for Disjunctive Datalog Programs
In this paper, a new technique for the optimization of (partially) bound
queries over disjunctive Datalog programs with stratified negation is
presented. The technique exploits the propagation of query bindings and extends
the Magic Set (MS) optimization technique.
An important feature of disjunctive Datalog is nonmonotonicity, which calls
for nondeterministic implementations, such as backtracking search. A
distinguishing characteristic of the new method is that the optimization can be
exploited also during the nondeterministic phase. In particular, after some
assumptions have been made during the computation, parts of the program may
become irrelevant to a query under these assumptions. This allows for dynamic
pruning of the search space. In contrast, the effect of the previously defined
MS methods for disjunctive Datalog is limited to the deterministic portion of
the process. In this way, the potential performance gain by using the proposed
method can be exponential, as could be observed empirically.
The correctness of MS is established thanks to a strong relationship between
MS and unfounded sets that has not been studied in the literature before. This
knowledge allows for extending the method also to programs with stratified
negation in a natural way.
The proposed method has been implemented in DLV and various experiments have
been conducted. Experimental results on synthetic data confirm the utility of
MS for disjunctive Datalog, and they highlight the computational gain that may
be obtained by the new method w.r.t. the previously proposed MS methods for
disjunctive Datalog programs. Further experiments on real-world data show the
benefits of MS within an application scenario that has received considerable
attention in recent years, the problem of answering user queries over possibly
inconsistent databases originating from integration of autonomous sources of
information.Comment: 67 pages, 19 figures, preprint submitted to Artificial Intelligenc
The Complexity of Datalog on Linear Orders
We study the program complexity of datalog on both finite and infinite linear
orders. Our main result states that on all linear orders with at least two
elements, the nonemptiness problem for datalog is EXPTIME-complete. While
containment of the nonemptiness problem in EXPTIME is known for finite linear
orders and actually for arbitrary finite structures, it is not obvious for
infinite linear orders. It sharply contrasts the situation on other infinite
structures; for example, the datalog nonemptiness problem on an infinite
successor structure is undecidable. We extend our upper bound results to
infinite linear orders with constants.
As an application, we show that the datalog nonemptiness problem on Allen's
interval algebra is EXPTIME-complete.Comment: 21 page
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