Inference to the stable explanations

Guido Governatori, Francesco Olivieri, Antonino Rotolo, Matteo Cristani

Research output: Book chapter/Published conference paperConference paperpeer-review

4 Citations (Scopus)


The process of explaining a piece of evidence by constructing a set of assumptions that are a good explanation for that evidence is ubiquitous in real-life (e.g. in legal systems). In this paper, we introduce, discuss, and formalise the notion of stable explanations in a non-monotonic setting. We show how, while applying it to the process of (1) computing a set of literals able to (2) derive a conclusion (3) from a set of defeasible rules, we obtain a restricted version of the notion of abduction. This is both interesting and useful: when an explanation for a given conclusion is stable, it can, in fact, be used to infer the same conclusion independently of other pieces of evidence that are found afterwards.

Original languageEnglish
Title of host publicationLogic Programming and Nonmonotonic Reasoning
Subtitle of host publication16th International Conference, LPNMR 2022, Genova, Italy, September 5–9, 2022, Proceedings
EditorsGeorg Gottlob, Daniela Inclezan, Marco Maratea
Place of PublicationCham, Switzerland
Number of pages14
ISBN (Electronic)9783031157073
ISBN (Print)9783031157066
Publication statusPublished - 2022
Event16th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2022 - Collegio Emiliani, Genova, Italy
Duration: 05 Sept 202209 Sept 2022 (Call for papers) (Conference website)

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13416 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2022
OtherLPNMR 2022 is the sixteenth in the series of international meetings on logic programming and non-monotonic reasoning. LPNMR is a forum for exchanging ideas on declarative logic programming, non-monotonic reasoning, and knowledge representation. The aim of the conference is to facilitate interactions between researchers and practitioners interested in the design and implementation of logic-based programming languages and database systems, and those working in knowledge representation and non-monotonic reasoning. LPNMR strives to encompass theoretical and experimental studies that have led or will lead to advances in declarative programming and knowledge representation, as well as their use in practical applications. A Doctoral Consortium will also be a part of the program.

LPNMR 2022 aims to bring together researchers from LPNMR core areas and application areas of the aforementioned kind in order to share research experiences, promote collaboration and identify directions for joint future research.
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