Design and results of the Fifth Answer Set Programming Competition

Abstract

Answer Set Programming (ASP) is a well-established paradigm of declarative programming that has been developed in the field of logic programming and nonmonotonic reasoning. Advances in ASP solving technology are customarily assessed in competition events, as it happens for other closely-related problemsolving technologies like SAT/SMT, QBF, Planning and Scheduling. ASP Competitions are (usually) biennial events; however, the Fifth ASP Competition departs from tradition, in order to join the FLoC Olympic Games at the Vienna Summer of Logic 2014, which is expected to be the largest event in the history of logic. This edition of the ASP Competition series is jointly organized by the University of Calabria (Italy), the Aalto University (Finland), and the University of Genova (Italy), and is affiliated with the 30th International Conference on Logic Programming (ICLP 2014). It features a completely re-designed setup, with novelties involving the design of tracks, the scoring schema, and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. Benchmark domains are taken from past editions, and best system packages submitted in 2013 are compared with new versions and solvers. * Also affiliated with the University of Potsdam, Germany.

A framework for easing the development of applications embedding answer set programming

“…It is worth noting that DLV was not available for Android; furthermore, it is natively implemented in C++, while the standard development process on Android is based on Java. To this end, DLV has been on purpose rebuilt using the NDK (Native Development Kit) 6 , and has been linked to the Java code using the JNI (Java Native Interface) 7 . This grants the access to the APIs provided by the Android NDK, and in turn accedes to the DLV exposed functionalities directly from the Java code of an Android application.…”

“…After more than twenty years of research, the theoretical properties of ASP are well understood and the solving technology, as evidenced by the availability of a number of robust and efficient systems [7], is mature for practical applications: ASP has been increasingly employed in many different domains, and also used for the development of industrial-level and enterprise applications [8,21]. Notably, this is spreading ASP teaching in universities worldwide, and, interestingly, is moving the focus from a strict theoretical scope to more practical aspects.…”

Constraints, lazy constraints, or propagators in ASP solving: An empirical analysis

“…In this way, it is possible to prevent the grounding of rules that are unnecessary for the computation. Albeit lazy grounding techniques obtained promising preliminary results, they cannot yet reach the performance of state of the art systems in many benchmarks (Calimeri et al 2016;Lefèvre and Nicolas 2009). One of the reasons is probably that fully-fledged lazy grounding techniques could not be easily integrated within solvers based on the very efficient Conflice-Driven Clause Learning (CDCL) algorithm (Silva and Sakallah 1999;Kaufmann et al 2016;Weinzierl 2017).…”

“…Nonetheless, there are some classes of programs (cf. (Calimeri et al 2016)) whose evaluation is not feasible with the "ground+solve" approach just because the grounding phase induces a combinatorial blow-up. An issue that is usually referred to as the grounding bottleneck of ASP.…”

Preface

“…Solvers were based on DPLL core, but a major breakthrough took place with the encoding of conflict-driven clause learning in solvers-for details, we refer to the paper by Silva and Sakallah (1999). The same idea was inherited by the ASP solver Clasp (Gebser et al 2009) that is currently the fastest ASP solver (according to the results of the ASP competition, organized since Calimeri et al 2016. The idea can be implemented in constraint solvers as well (Stuckey 2010), and it is proved to be effective in the Constraint Programming competitions (MiniZinc Challenge, organized since 2008Stuckey et al 2014, although for this framework excellent implementations of global constraints can still be more effective.…”