1,400 research outputs found
Hybrid Tractable Classes of Binary Quantified Constraint Satisfaction Problems
In this paper, we investigate the hybrid tractability of binary Quantified
Constraint Satisfaction Problems (QCSPs). First, a basic tractable class of
binary QCSPs is identified by using the broken-triangle property. In this
class, the variable ordering for the broken-triangle property must be same as
that in the prefix of the QCSP. Second, we break this restriction to allow that
existentially quantified variables can be shifted within or out of their
blocks, and thus identify some novel tractable classes by introducing the
broken-angle property. Finally, we identify a more generalized tractable class,
i.e., the min-of-max extendable class for QCSPs
Tractability in Constraint Satisfaction Problems: A Survey
International audienceEven though the Constraint Satisfaction Problem (CSP) is NP-complete, many tractable classes of CSP instances have been identified. After discussing different forms and uses of tractability, we describe some landmark tractable classes and survey recent theoretical results. Although we concentrate on the classical CSP, we also cover its important extensions to infinite domains and optimisation, as well as #CSP and QCSP
Generalized Majority-Minority Operations are Tractable
Generalized majority-minority (GMM) operations are introduced as a common
generalization of near unanimity operations and Mal'tsev operations on finite
sets. We show that every instance of the constraint satisfaction problem (CSP),
where all constraint relations are invariant under a (fixed) GMM operation, is
solvable in polynomial time. This constitutes one of the largest tractable
cases of the CSP
Certainty Closure: Reliable Constraint Reasoning with Incomplete or Erroneous Data
Constraint Programming (CP) has proved an effective paradigm to model and
solve difficult combinatorial satisfaction and optimisation problems from
disparate domains. Many such problems arising from the commercial world are
permeated by data uncertainty. Existing CP approaches that accommodate
uncertainty are less suited to uncertainty arising due to incomplete and
erroneous data, because they do not build reliable models and solutions
guaranteed to address the user's genuine problem as she perceives it. Other
fields such as reliable computation offer combinations of models and associated
methods to handle these types of uncertain data, but lack an expressive
framework characterising the resolution methodology independently of the model.
We present a unifying framework that extends the CP formalism in both model
and solutions, to tackle ill-defined combinatorial problems with incomplete or
erroneous data. The certainty closure framework brings together modelling and
solving methodologies from different fields into the CP paradigm to provide
reliable and efficient approches for uncertain constraint problems. We
demonstrate the applicability of the framework on a case study in network
diagnosis. We define resolution forms that give generic templates, and their
associated operational semantics, to derive practical solution methods for
reliable solutions.Comment: Revised versio
Variable and value elimination in binary constraint satisfaction via forbidden patterns
Variable or value elimination in a constraint satisfaction problem (CSP) can
be used in preprocessing or during search to reduce search space size. A
variable elimination rule (value elimination rule) allows the polynomial-time
identification of certain variables (domain elements) whose elimination,
without the introduction of extra compensatory constraints, does not affect the
satisfiability of an instance. We show that there are essentially just four
variable elimination rules and three value elimination rules defined by
forbidding generic sub-instances, known as irreducible existential patterns, in
arc-consistent CSP instances. One of the variable elimination rules is the
already-known Broken Triangle Property, whereas the other three are novel. The
three value elimination rules can all be seen as strict generalisations of
neighbourhood substitution.Comment: A full version of an IJCAI'13 paper to appear in Journal of Computer
and System Sciences (JCSS
A Trichotomy in the Complexity of Counting Answers to Conjunctive Queries
Conjunctive queries are basic and heavily studied database queries; in
relational algebra, they are the select-project-join queries. In this article,
we study the fundamental problem of counting, given a conjunctive query and a
relational database, the number of answers to the query on the database. In
particular, we study the complexity of this problem relative to sets of
conjunctive queries. We present a trichotomy theorem, which shows essentially
that this problem on a set of conjunctive queries is either tractable,
equivalent to the parameterized CLIQUE problem, or as hard as the parameterized
counting CLIQUE problem; the criteria describing which of these situations
occurs is simply stated, in terms of graph-theoretic conditions
Broken triangles: From value merging to a tractable class of general-arity constraint satisfaction problems
International audienceA binary CSP instance satisfying the broken-triangle property (BTP) can be solved in polynomial time. Unfortunately, in practice, few instances satisfy the BTP. We show that a local version of the BTP allows the merging of domain values in arbitrary instances of binary CSP, thus providing a novel polynomial-time reduction operation. Extensive experimental trials on benchmark instances demonstrate a significant decrease in instance size for certain classes of problems. We show that BTP-merging can be generalised to instances with constraints of arbitrary arity and we investigate the theoretical relationship with resolution in SAT. A directional version of general-arity BTP-merging then allows us to extend the BTP tractable class previously defined only for binary CSP. We investigate the complexity of several related problems including the recognition problem for the general-arity BTP class when the variable order is unknown, finding an optimal order in which to apply BTP merges and detecting BTP-merges in the presence of global constraints such as AllDifferent
The Complexity of Satisfiability for Sub-Boolean Fragments of ALC
The standard reasoning problem, concept satisfiability, in the basic
description logic ALC is PSPACE-complete, and it is EXPTIME-complete in the
presence of unrestricted axioms. Several fragments of ALC, notably logics in
the FL, EL, and DL-Lite family, have an easier satisfiability problem;
sometimes it is even tractable. All these fragments restrict the use of Boolean
operators in one way or another. We look at systematic and more general
restrictions of the Boolean operators and establish the complexity of the
concept satisfiability problem in the presence of axioms. We separate tractable
from intractable cases.Comment: 17 pages, accepted (in short version) to Description Logic Workshop
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