Belief merging with the aim of truthlikeness

Synthese 193 (7):2013-2034 (2016)
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Abstract

The merging/fusion of belief/data collections in propositional logic form is a topic that has received due attention within the domains of database and AI research. A distinction can be made between two types of scenarios to which the process of merging can be applied. In the first type, the collections represent preferences, such as the voting choices of a group of people, that need to be aggregated so as to give a consistent result that in some way best represents the collective judgement of the group. In the second type, the collections represent factual data that is to be aggregated with an aim of obtaining a result that maximises factual correctness. After introducing a general framework for belief merging via some prominent literature on the topic, this paper then introduces and considers a method for belief merging with the second type of scenario in mind. Its suitability is corroborated by demonstrating how it can be seen as a special case of a merging procedure that combines aggregation of probabilities and maximisation of expected truthlikeness

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Simon D'Alfonso
University of Melbourne (PhD)

Citations of this work

A Scientific Metaphysical Naturalisation of Information.Bruce Long - 2018 - Dissertation, University of Sydney

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References found in this work

Likeness to Truth.Graham Oddie - 1986 - Dordrecht and Boston: Reidel.
Truthlikeness.I. Niiniluoto - 2006 - In Sahotra Sarkar & Jessica Pfeifer (eds.), The Philosophy of Science: An Encyclopedia. Routledge. pp. 854--857.
Verisimilitude: The third period.Ilkka Niiniluoto - 1998 - British Journal for the Philosophy of Science 49 (1):1-29.
Truthlikeness.Graham Oddie - 2014 - Stanford Encyclopedia.
Truthlikeness.G. Oddie - 2008 - In Martin P. Curd (ed.), The Routledge Companion to Philosophy of Science. pp. 478--488.

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