Parallel Belief Contraction via Order Aggregation

Fuente: arXiv
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Auteurs principaux: Chandler, Jake, Booth, Richard
Format: Preprint
Publié: 2025
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author Chandler, Jake
Booth, Richard
author_facet Chandler, Jake
Booth, Richard
contents The standard ``serial'' (aka ``singleton'') model of belief contraction models the manner in which an agent's corpus of beliefs responds to the removal of a single item of information. One salient extension of this model introduces the idea of ``parallel'' (aka ``package'' or ``multiple'') change, in which an entire set of items of information are simultaneously removed. Existing research on the latter has largely focussed on single-step parallel contraction: understanding the behaviour of beliefs after a single parallel contraction. It has also focussed on generalisations to the parallel case of serial contraction operations whose characteristic properties are extremely weak. Here we consider how to extend serial contraction operations that obey stronger properties. Potentially more importantly, we also consider the iterated case: the behaviour of beliefs after a sequence of parallel contractions. We propose a general method for extending serial iterated belief change operators to handle parallel change based on an n-ary generalisation of Booth & Chandler's TeamQueue binary order aggregators.
format Preprint
id arxiv_https___arxiv_org_abs_2501_13295
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Parallel Belief Contraction via Order Aggregation
Chandler, Jake
Booth, Richard
Artificial Intelligence
I.2.4
The standard ``serial'' (aka ``singleton'') model of belief contraction models the manner in which an agent's corpus of beliefs responds to the removal of a single item of information. One salient extension of this model introduces the idea of ``parallel'' (aka ``package'' or ``multiple'') change, in which an entire set of items of information are simultaneously removed. Existing research on the latter has largely focussed on single-step parallel contraction: understanding the behaviour of beliefs after a single parallel contraction. It has also focussed on generalisations to the parallel case of serial contraction operations whose characteristic properties are extremely weak. Here we consider how to extend serial contraction operations that obey stronger properties. Potentially more importantly, we also consider the iterated case: the behaviour of beliefs after a sequence of parallel contractions. We propose a general method for extending serial iterated belief change operators to handle parallel change based on an n-ary generalisation of Booth & Chandler's TeamQueue binary order aggregators.
title Parallel Belief Contraction via Order Aggregation
topic Artificial Intelligence
I.2.4
url https://arxiv.org/abs/2501.13295