Algorithm selection techniques are known to improve the performance of systems for several knowledge representation and reasoning frameworks.This holds also in the case of Answer Set Programming (ASP), which is a rule-based programming paradigm with roots in logic programming and non-monotonic reasoning. Indeed, the multi-engine approach to ASP solving implemented in
was particularly effective on the instances of the third ASP competition. In this paper we report about the advances we made on
in order to deal with the new standard language ASPCore 2.0, which substantially extends the previous version of the standard language.An experimental analysis conducted on the Fifth ASP Competition benchmarks and solvers confirms the effectiveness of our approach also in comparison to rival systems.
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