Parallel Belief Revision via Order Aggregation

Parallel Belief Revision via Order Aggregation

Jake Chandler, Richard Booth

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Main Track. Pages 4419-4426. https://doi.org/10.24963/ijcai.2025/492

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.
Keywords:
Knowledge Representation and Reasoning: KRR: Belief change
Game Theory and Economic Paradigms: GTEP: Computational social choice