Modelling Iterative Judgment Aggregation

Abstract

We introduce a formal model of iterative judgment aggregation, enabling the analysis of scenarios in which agents repeatedly update their individual positions on a set of issues, before a final decision is made by applying an aggregation rule to these individual positions. Focusing on two popular aggregation rules, the premise-based rule and the plurality rule, we study under what circumstances convergence to an equilibrium can be guaranteed. We also analyse the quality, in social terms, of the final decisions obtained. Our results not only shed light on the parameters that determine whether iteration converges and is socially beneficial, but they also clarify important differences between iterative judgment aggregation and the related framework of iterative voting.

Cite

Text

Terzopoulou and Endriss. "Modelling Iterative Judgment Aggregation." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.11440

Markdown

[Terzopoulou and Endriss. "Modelling Iterative Judgment Aggregation." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/terzopoulou2018aaai-modelling/) doi:10.1609/AAAI.V32I1.11440

BibTeX

@inproceedings{terzopoulou2018aaai-modelling,
  title     = {{Modelling Iterative Judgment Aggregation}},
  author    = {Terzopoulou, Zoi and Endriss, Ulle},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {1234-1241},
  doi       = {10.1609/AAAI.V32I1.11440},
  url       = {https://mlanthology.org/aaai/2018/terzopoulou2018aaai-modelling/}
}