Answer Set Programming (ASP) is a well-established AI formalism rooted in nonmonotonic reasoning. Paracoherent semantics for ASP have been proposed to derive useful conclusions also in the absence of answer sets caused by cyclic default negation. Recently, several different algorithms have been proposed to implement them, but no algorithm is always preferable to the others in all instances. In this paper, we apply algorithm selection techniques to devise a more efficient paracoherent answer set solver combining existing algorithms. The effectiveness of the approach is demonstrated empirically running our system on existing benchmarks.
Algorithm Selection for Paracoherent Answer Set Computation / Amendola, Giovanni; Dodaro, Carmine; Faber, Wolfgang; Pulina, Luca; Ricca, Francesco. - 11468:(2019), pp. 479-489. (Intervento presentato al convegno 16th European Conference on Logics in Artificial Intelligence, JELIA 2019 tenutosi a ita nel 2019) [10.1007/978-3-030-19570-0_31].
Algorithm Selection for Paracoherent Answer Set Computation
Pulina, Luca;
2019-01-01
Abstract
Answer Set Programming (ASP) is a well-established AI formalism rooted in nonmonotonic reasoning. Paracoherent semantics for ASP have been proposed to derive useful conclusions also in the absence of answer sets caused by cyclic default negation. Recently, several different algorithms have been proposed to implement them, but no algorithm is always preferable to the others in all instances. In this paper, we apply algorithm selection techniques to devise a more efficient paracoherent answer set solver combining existing algorithms. The effectiveness of the approach is demonstrated empirically running our system on existing benchmarks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
