Logo des Repositoriums
 

A Practical Comparison of Qualitative Inferences with Preferred Ranking Models

dc.contributor.authorBeierle, Christoph
dc.contributor.authorEichhorn, Christian
dc.contributor.authorKutsch, Steven
dc.date.accessioned2018-01-08T08:12:56Z
dc.date.available2018-01-08T08:12:56Z
dc.date.issued2017
dc.description.abstractWhen reasoning qualitatively from a conditional knowledge base, two established approaches are system Z and p-entailment. The latter infers skeptically over all ranking models of the knowledge base, while system Z uses the unique pareto-minimal ranking model for the inference relations. Between these two extremes of using all or just one ranking model, the approach of c-representations generates a subset of all ranking models with certain constraints. Recent work shows that skeptical inference over all c-representations of a knowledge base includes and extends p-entailment. In this paper, we follow the idea of using preferred models of the knowledge base instead of the set of all models as a base for the inference relation. We employ different minimality constraints for c-representations and demonstrate inference relations from sets of preferred c-representations with respect to these constraints. We present a practical tool for automatic c-inference that is based on a high-level, declarative constraint-logic programming approach. Using our implementation, we illustrate that different minimality constraints lead to inference relations that differ mutually as well as from system Z and p-entailment.
dc.identifier.pissn1610-1987
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/11044
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 31, No. 1
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectC-inference
dc.subjectC-representation
dc.subjectConditional logic
dc.subjectDefault rule
dc.subjectP-entailment
dc.subjectQualitative conditional
dc.subjectRanking function
dc.subjectSystem Z
dc.titleA Practical Comparison of Qualitative Inferences with Preferred Ranking Models
dc.typeText/Journal Article
gi.citation.endPage52
gi.citation.startPage41

Dateien