60 research outputs found
Reducing fuzzy answer set programming to model finding in fuzzy logics
In recent years, answer set programming (ASP) has been extended to deal with multivalued predicates. The resulting formalisms allow for the modeling of continuous problems as elegantly as ASP allows for the modeling of discrete problems, by combining the stable model semantics underlying ASP with fuzzy logics. However, contrary to the case of classical ASP where many efficient solvers have been constructed, to date there is no efficient fuzzy ASP solver. A well-known technique for classical ASP consists of translating an ASP program P to a propositional theory whose models exactly correspond to the answer sets of P. In this paper, we show how this idea can be extended to fuzzy ASP, paving the way to implement efficient fuzzy ASP solvers that can take advantage of existing fuzzy logic reasoners
Consistent Query Answers in the Presence of Universal Constraints
The framework of consistent query answers and repairs has been introduced to
alleviate the impact of inconsistent data on the answers to a query. A repair
is a minimally different consistent instance and an answer is consistent if it
is present in every repair. In this article we study the complexity of
consistent query answers and repair checking in the presence of universal
constraints.
We propose an extended version of the conflict hypergraph which allows to
capture all repairs w.r.t. a set of universal constraints. We show that repair
checking is in PTIME for the class of full tuple-generating dependencies and
denial constraints, and we present a polynomial repair algorithm. This
algorithm is sound, i.e. always produces a repair, but also complete, i.e.
every repair can be constructed. Next, we present a polynomial-time algorithm
computing consistent answers to ground quantifier-free queries in the presence
of denial constraints, join dependencies, and acyclic full-tuple generating
dependencies. Finally, we show that extending the class of constraints leads to
intractability. For arbitrary full tuple-generating dependencies consistent
query answering becomes coNP-complete. For arbitrary universal constraints
consistent query answering is \Pi_2^p-complete and repair checking
coNP-complete.Comment: Submitted to Information System
A Preference-Based Approach to Backbone Computation with Application to Argumentation
The backbone of a constraint satisfaction problem consists of those variables that take the same value in all solutions. Algorithms for determining the backbone of propositional formulas, i.e., Boolean satisfiability (SAT) instances, find various real-world applications. From the knowledge representation and reasoning (KRR) perspective, one interesting connection is that of backbones and the so-called ideal semantics in abstract argumentation. In this paper, we propose a new backbone algorithm which makes use of a "SAT with preferences" solver, i.e., a SAT solver which is guaranteed to output a most preferred satisfying assignment w.r.t. a given preference over literals of the SAT instance at hand. We also show empirically that the proposed approach is specifically effective in computing the ideal semantics of argumentation frameworks, noticeably outperforming an other state-of-the-art backbone solver as well as the winning approach of the recent ICCMA 2017 argumentation solver competition in the ideal semantics track.Peer reviewe
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