Answer Set Programming (ASP) is a branch of Logic Programming particularly useful for representing complex domains. Logic abduction, the reasoning strategy that deals with incomplete data, is tightly related to ASP, and encodes incompleteness through abducibles. The goal of logic abduction is to find the minimal set of abducibles (where minimality is usually considered in terms of set inclusion) that explains a query. Recently, abductive reasoning has been introduced in the context of Probabilistic Logic Programming, but no solutions are available for Probabilistic Answer Set Programming (PASP). In this paper, we close this gap and propose an algorithm to perform abduction both in ASP and in PASP.

Abduction in (Probabilistic) Answer Set Programming

Azzolini D.
;
Bellodi E.;Riguzzi F.
2022

Abstract

Answer Set Programming (ASP) is a branch of Logic Programming particularly useful for representing complex domains. Logic abduction, the reasoning strategy that deals with incomplete data, is tightly related to ASP, and encodes incompleteness through abducibles. The goal of logic abduction is to find the minimal set of abducibles (where minimality is usually considered in terms of set inclusion) that explains a query. Recently, abductive reasoning has been introduced in the context of Probabilistic Logic Programming, but no solutions are available for Probabilistic Answer Set Programming (PASP). In this paper, we close this gap and propose an algorithm to perform abduction both in ASP and in PASP.
2022
Abduction
Probabilistic Answer Set Programming
Statistical Relational Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2494793
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