Maratea, Marco and Pulina, Luca and Ricca, Francesco (08 October 2012) Multi-engine ASP solving with policy adaptation. Alghero, University of Sassari - Computer Vision Laboratory. p. 24 (CVL 2012/004). Technical Report.
The recent application of Machine Learning techniques to the Answer Set Programming (ASP) field proved to be effective. In particular, the multi-engine ASP solver ME-ASP is efficient: it is able to solve more instances than any other ASP system that participated to the 3rd ASP Competition on the "System Track" benchmarks. In the ME-ASP approach, classification methods inductively learn off-line algorithm selection policies starting from both a set of features of instances in a training set,
and the solvers performance on such instances.
I documenti depositati in UnissResearch sono protetti dalle leggi che regolano il diritto d'autore
Repository Staff Only: item control page