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Incremental Answer Set Programming with Overgrounding

Published online by Cambridge University Press:  20 September 2019

FRANCESCO CALIMERI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: lastname@mat.unical.it)-https://www.mat.unical.it
GIOVAMBATTISTA IANNI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: lastname@mat.unical.it)-https://www.mat.unical.it
FRANCESCO PACENZA
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: lastname@mat.unical.it)-https://www.mat.unical.it
SIMONA PERRI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: lastname@mat.unical.it)-https://www.mat.unical.it
JESSICA ZANGARI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Italy (e-mail: lastname@mat.unical.it)-https://www.mat.unical.it

Abstract

Repeated executions of reasoning tasks for varying inputs are necessary in many applicative settings, such as stream reasoning. In this context, we propose an incremental grounding approach for the answer set semantics. We focus on the possibility of generating incrementally larger ground logic programs equivalent to a given non-ground one; so called overgrounded programs can be reused in combination with deliberately many different sets of inputs. Updating overgrounded programs requires a small effort, thus making the instantiation of logic programs considerably faster when grounding is repeated on a series of inputs similar to each other. Notably, the proposed approach works “under the hood”, relieving designers of logic programs from controlling technical aspects of grounding engines and answer set systems. In this work we present the theoretical basis of the proposed incremental grounding technique, we illustrate the consequent repeated evaluation strategy and report about our experiments.

Type
Original Article
Copyright
© Cambridge University Press 2019 

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