---
title: "Parallel Belief Revision via Order Aggregation"
authors:
  - "Jake Chandler"
  - "Richard Booth"
doi: "10.24963/ijcai.2025/492"
url: "https://ijcai.org/proceedings/2025/492"
pdf: "https://ijcai.org/proceedings/2025/0492.pdf"
venue: "Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"
year: 2025
pages: "4419-4426"
track: "Main Track"
keywords:
  - "Knowledge Representation and Reasoning: KRR: Belief change"
  - "Game Theory and Economic Paradigms: GTEP: Computational social choice"
---

# Parallel Belief Revision via Order Aggregation

Jake Chandler, Richard Booth

*Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence*, pages 4419-4426. DOI: [10.24963/ijcai.2025/492](https://doi.org/10.24963/ijcai.2025/492)

## Abstract

Despite efforts to better understand the constraints that operate on single-step parallel (aka ``package'', ``multiple'') revision, very little work has been carried out on how to extend the model to the iterated case. A recent paper by Delgrande & Jin outlines a range of relevant rationality postulates. While many of these are plausible, they lack an underlying unifying explanation. We draw on recent work on iterated parallel contraction to offer a general method for extending serial iterated belief revision operators to handle parallel change. This method, based on a family of order aggregators known as TeamQueue aggregators, provides a principled way to recover the independently plausible properties that can be found in the literature, without yielding the more dubious ones.