Ranking kinematics for revising by contextual information

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dc.contributor.authorSezgin, Meliha
dc.contributor.authorKern-Isberner, Gabriele
dc.contributor.authorBeierle, Christoph
dc.date.accessioned2022-03-14T14:53:15Z
dc.date.available2022-03-14T14:53:15Z
dc.date.issued2021-05-28
dc.description.abstractProbability kinematics is a leading paradigm in probabilistic belief change. It is based on the idea that conditional beliefs should be independent from changes of their antecedents’ probabilities. In this paper, we propose a re-interpretation of this paradigm for Spohn’s ranking functions which we call Generalized Ranking Kinematics as a new principle for iterated belief revision of ranking functions by sets of conditional beliefs with respect to their specific subcontext. By taking into account semantical independencies, we can reduce the complexity of the revision task to local contexts. We show that global belief revision can be set up from revisions on the local contexts via a merging operator. Furthermore, we formalize a variant of the Ramsey-Test based on the idea of local contexts which connects conditional and propositional revision in a straightforward way. We extend the belief change methodology of c-revisions to strategic c-revisions which will serve as a proof of concept.en
dc.identifier.urihttp://hdl.handle.net/2003/40792
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-22649
dc.language.isoende
dc.relation.ispartofseriesAnnals of mathematics and artificial intelligence;Vol. 89. 2021, pp 1101–1131
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectIterated belief revisionen
dc.subjectKinematicsen
dc.subjectSpohn’s ranking functionsen
dc.subjectJeffrey’s ruleen
dc.subject.ddc004
dc.subject.rswkKinematikde
dc.titleRanking kinematics for revising by contextual informationen
dc.typeTextde
dc.type.publicationtypearticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationAnnals of mathematics and artificial intelligence. Vol. 89. 2021, pp 1101-1131en
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1007/s10472-021-09746-2de

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