Taming Dilation in Imprecise Pooling

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

If an agent’s belief in a proposition is represented by imprecise probabilities, i.e. intervals of probability values, a phenomenon called dilation can occur, where updating the agent’s belief with a new observation can only widen the probability interval, thus making the agent more uncertain, regardless of the observation made. Similar to standard updating, dilation can also occur in the context of imprecise opinion pooling, where the imprecise beliefs of multiple agents are aggregated. In this work, we provide the first formal investigation of dilation and its counterpart, contraction, in the context of imprecise opinion pooling. To this end, we use a recently defined voting rule, Voting for Bins (VfB), as a means to handle dilation and contraction, consistent with intuitions about the quality of additional opinions. VfB, inspired by the Condorcet Jury Theorem (CJT), is extended to account for correlation by an opinion leader. This model is further generalized to account for average correlation.

Details

OriginalspracheEnglisch
TitelPRIMA 2024: Principles and Practice of Multi-Agent Systems
Redakteure/-innenRyuta Arisaka, Takayuki Ito, Victor Sanchez-Anguix, Sebastian Stein, Reyhan Aydoğan, Leon van der Torre
Herausgeber (Verlag)Springer, Cham
Seiten428–443
Seitenumfang16
ISBN (elektronisch)978-3-031-77367-9
ISBN (Print)978-3-031-77366-2
PublikationsstatusVeröffentlicht - 2024
Peer-Review-StatusJa

Publikationsreihe

ReiheLecture Notes in Computer Science
Band15395
ISSN0302-9743
ReiheLecture Notes in Artificial Intelligence (LNAI)
ISSN0302-9743

Externe IDs

Scopus 85210145247

Schlagworte

Schlagwörter

  • Dilation, Jury Theorem, Multi-Agent Opinion Pooling