IJCAI 2021poster26 citations

Dynamic Proportional Rankings

Jonas Israel, Markus Brill

Abstract

Proportional ranking rules aggregate approval-style preferences of agents into a collective ranking such that groups of agents with similar preferences are adequately represented. Motivated by the application of live Q&A platforms, where submitted questions need to be ranked based on the interests of the audience, we study a dynamic extension of the proportional rankings setting. In our setting, the goal is to maintain the proportionality of a ranking when alternatives (i.e., questions)---not necessarily from the top of the ranking---get selected sequentially. We propose generalizations of well-known aggregation rules to this setting and study their monotonicity and proportionality properties. We also evaluate the performance of these rules experimentally, using realistic probabilistic assumptions on the selection procedure.

Agent-based and Multi-agent Systems: Computational Social ChoiceAgent-based and Multi-agent Systems: Voting
BibTeX
@inproceedings{ijcai2021p37,
  title     = {Dynamic Proportional Rankings},
  author    = {Israel, Jonas and Brill, Markus},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Zhi-Hua Zhou},
  pages     = {261--267},
  year      = {2021},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2021/37},
  url       = {https://doi.org/10.24963/ijcai.2021/37},
}
Dynamic Proportional Rankings · IJCAI 2021