Guohui Xiao

The Fourth Answer Set Programming Competition: Preliminary Report

Answer Set Programming is a well-established paradigm of declarative programming in close relationship with other declarative formalisms such as SAT Modulo Theories, Constraint Handling Rules, PDDL and many others. Since its first informal editions, ASP systems are compared in the nowadays customary ASP Competition. The fourth ASP Competition, held in 2012/2013, is the sequel to previous editions and it was jointly organized by University of Calabria Italy and the Vienna University of Technology Austria. Participants competed on a selected collection of benchmark problems, taken from a variety of research areas and real world applications. The Competition featured two tracks: the Model& Solve Track, held on an open problem encoding, on an open language basis, and open to any kind of system based on a declarative specification paradigm; and the System Track, held on the basis of fixed, public problem encodings, written in a standard ASP language.

Inconsistency measurement based on variables in minimal unsatisfiable subsets

Measuring inconsistency degrees of knowledge bases (KBs) provides important context information for facilitating inconsistency handling. Several semantic and syntax based measures have been proposed separately. n nIn this paper, we propose a new way to define inconsistency measurements by combining semantic and syntax based approaches. It is based on counting the variables of minimal unsatisfiable subsets (MUSes) and minimal correction subsets (MCSes), which leads to two equivalent inconsistency degrees, named IDMUS and IDMCS. We give the theoretical and experimental comparisons between them and two purely semantic-based inconsistency degrees: 4-valued and the Quasi Classical semantics based inconsistency degrees. Moreover, the computational complexities related to our new inconsistency measurements are studied. As it turns out that computing the exact inconsistency degrees is intractable in general, we then propose and evaluate an anytime algorithm to make IDMUS and IDMCS usable in knowledge management applications. In particular, as most of syntax based measures tend to be difficult to compute in reality due to the exponential number of MUSes, our new inconsistency measures are practical because the numbers of variables in MUSes are often limited or easily to be approximated. n nWe evaluate our approach on the DC benchmark. Our encouraging experimental results show that these new inconsistency measurements or their approximations are efficient to handle large knowledge bases and to better distinguish inconsistent knowledge bases.

Uniform evaluation of nonmonotonic DL-Programs

Nonmonotonic description logic programs are a major formalism for a loose coupling of rules and ontologies, formalized in logic programming and description logics, respectively. While this approach is attractive for combining systems, the impedance mismatch between different reasoning engines and the API-style interfacing are an obstacle to efficient evaluation of dl-programs in general. Uniform evaluation circumvents this by transforming programs into a single formalism, which can be evaluated on a single reasoning engine. In this paper, we consider recent and ongoing work on this approach which uses relational first-order logic (and thus relational database engines) and datalog with negation as target formalisms. Experimental data show that significant performance gains are possible and suggest the potential of this approach.

The DReW System for Nonmonotonic DL-Programs

Nonmonotonic DL-programs provide a loose integration of Description Logic (DL) ontologies and Logic Programming (LP) rules with negation, where a rule engine can query an ontology with a native DL reasoner. However, in most systems for DL-programs, the overhead of an external DL reasoner might be considerable. Datalog-rewritable DL ontologies, such as most fragments of OWL 2 RL, OWL 2 EL, and OWL 2 QL, can be rewritten to Datalog programs, so that DL-programs can be reduced to Datalog ¬ , i.e., Datalog with negation, under both well-founded and answer set semantics. We developed the reasoner DReW that uses the Datalog-rewriting technique. In addition to DL-programs, DReW can also answer conjunctive queries under DL-safeness conditions over Datalog-rewritable ontologies as well as reason on terminological default logics over such ontologies.

Inline Evaluation of Hybrid Knowledge Bases

The deployment of knowledge representation formalisms to the Web has created the need for hybrid formalisms that combine heterogeneous knowledge bases. The aim of this research is to improve the reasoning efficiency over hybrid knowledge bases (KBs). The traditional way of reasoning over hybrid KBs is to use different underlying reasoners to access the different data sources, which causes overhead. To remedy this, we propose a new strategy, called inline evaluation, which compiles the whole hybrid KB into a new KB using only one single formalism. Hence we can use a single reasoner to do the reasoning tasks, and improve the efficiency of hybrid reasoning.

VCWC: A Versioning Competition Workflow Compiler

System competitions evaluate solvers and compare state-of-the-art implementations on benchmark sets in a dedicated and controlled computing environment, usually comprising of multiple machines. Recent initiatives such as [6] aim at establishing best practices in computer science evaluations, especially identifying measures to be taken for ensuring repeatability, excluding common pitfalls, and introducing appropriate tools. For instance, Asparagus [1] focusses on maintaining benchmarks and instances thereof. Other known tools such as Runlim http://fmv.jku.at/runlim/ and Runsolver [12] help to limit resources and measure CPU time and memory usage of solver runs. Other systems are tailored at specific needs of specific communities: the not publicly accessible ASP Competition evaluation platform for the 3rd ASP Competition 2011 [4] implements a framework for running a ASP competition. Another more general platform is StarExec [13], which aims at providing a generic framework for competition maintainers. The last two systems are similar in spirit, but each have restrictions that reduce the possibility of general usage: the StarExec platform does not provide support for generic solver input and has no scripting support, while the ASP Competition evaluation platform has no support for fault-tolerant execution of instance runs.Moreover, benchmark statistics and ranking can only be computed after all solver runs for all benchmark instances have been completed.