- Rachael Colley, Théo Delemazure and Hugo Gilbert. Measuring a Priori Voting Power in Liquid Democracy. IJCAI. 2023. [Working paper]
- Rachael Colley, Umberto Grandi, César A Hidalgo, Mariana Macedo and Carlos Navarrete. Measuring and Controlling Divisiveness in Rank Aggregation. IJCAI. 2023.
- Rachael Colley, Théo Delemazure and Hugo Gilbert. Measuring a Priori Voting Power – Taking Delegations Seriously (Extended Abstract). AAMAS. 2023. [Full paper]
- Rachael Colley and Umberto Grandi. The Spread of Opinions via Boolean Networks. EUMAS. 2022.
- Rachael Colley and Umberto Grandi. Preserving consistency in multi-issue liquid democracy. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI). 2022.
- Joseph Boudou, Rachael Colley and Umberto Grandi. Itero: An online iterative voting application. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI). 2022.
- Rachael Colley, Umberto Grandi and Arianna Novaro. Unravelling multi-agent ranked delegations. Auton Agent Multi-Agent Syst 36, 9. 2022.
- Rachael Colley. Multi-Agent Ranked Delegations in Voting. (Doctoral Consortium) In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS). 2021.
- Rachael Colley, Umberto Grandi, and Arianna Novaro. Smart Voting. In Proceeding of the 29th International Joint Conference on Artificial Intelligence (IJCAI). 2020.
Working Papers
- Carlos Navarrete Lizama, Nicole Ferrada, Mariana Gomes da Motta Macedo, Rachael Colley, Jingling Zhang, Umberto Grandi, Jérôme Lang, César A Hidalgo. Understanding Political Agreements and Disagreements: Evidence from the 2022 French Presidential Election.
- Manon Revel, Niclas Boehmer, Rachael Colley, Markus Brill, Piotr Faliszewski, Edith Elkind. Selecting Representative Bodies: An Axiomatic View.
- Linus Boes, Rachael Colley, Umberto Grandi, Jérôme Lang and Arianna Novaro. Collective Discrete Optimisation as Judgment Aggregation. [Presented at M-Pref2022]
Master’s Thesis
Guaranteeing Feasible Outcomes in Judgment Aggregation