The Second Answer Set Programming Competition

Abstract

This paper reports on the Second Answer Set Programming Competition. The competitions in areas of Satisfiability checking, Pseudo-Boolean constraint solving and Quantified Boolean Formula evaluation have proven to be a strong driving force for a community to develop better performing systems. Following this experience, the Answer Set Programming competition series was set up in 2007, and ran as part of the International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR). This second competition, held in conjunction with LPNMR 2009, differed from the first one in two important ways. First, while the original competition was restricted to systems designed for the answer set programming language, the sequel was open to systems designed for other modeling languages, as well. Consequently, among the contestants of the second competition were a CLP(FD) team and three model generation systems for (extensions of) classical logic. Second, this latest competition covered not only satisfiability problems but also optimization ones. We present and discuss the set-up and the results of the competition.

The Intelligent Grounder of DLV

“…In addition, the system incorporates several front-ends for dealing with specific applications. Concerning efficiency, DLV is competitive with the most advanced systems in the area of ASP, as confirmed also by the results of the First and Second ASP System Competitions [16,10], in which DLV won the MGS (Modeling, Grounding, Solving) category and the class of decision problems in P, respectively. DLV did not participate in the most recent competition [6], as the project team was organizing the event.…”

The system Kato: Detecting cases of plagiarism for answer-set programs

“…Without going into details, the problem of finding variable or predicate substitutions is related to the homomorphism problem for relational structures which is known to be NP-complete (when formulated as a decision problem). However, high complexity of the involved reasoning tasks does not turn out to be a bottle-neck of our approach since this worst-case complexity is relative to the size of rules or programs and problem encodings in ASP tend to be quite concise and rarely involve a larger number of rules-this is witnessed, e.g., by the collection of benchmark programs used for the recent ASP solver competition (Denecker et al 2009). …”

Stepping through an Answer-Set Program

“…We will use the maze-generation problem, a benchmark problem from the second ASP competition [9], as a running example. The task is to generate a two-dimensional grid where each cell is either a wall or empty.…”