Group decision making (GDM) is a central activity of human interaction, and also an increasingly important issue in computer science with applications such as multi-agent systems, preference aggregation in artificial intelligence, e-democracy platforms, and group recommender systems. This research project is situated in the field of computational social choice (COMSOC), which is concerned with the study of GDM from a computational point of view. The main focus of this project lies on sustainable, long-term, algorithm-supported GDM within small or medium-sized groups that decide about a varying range of topics.
Instead of considering decisions as singular events, we want to take the history of past group decisions into account. This novel viewpoint allows us to tackle a fundamental issue of GDM: how to avoid situations where frustrated participants drop out of the decision making process. For example, if a minority has been repeatedly overruled in the past, it might withdraw from the decision process. To overcome this problem, we will introduce and analyze perpetual voting rules: these are voting rules that take the history of previous decisions into account and guarantee fairness across this history.
The overall goal of this project is to find GDM algorithms that foster participation and make the GDM process long-term sustainable. To achieve this goal, we will use a large array of methods established in computational social choice. The outcome of this project contributes to a future in which GDM apps and e-democracy systems have "COMSOC inside", and hence make use of the theoretical and experimental expertise established in this field. The perspectives of the proposed research—long-term GDM, compromise, and reduced information requirements—are essential ingredients for sustaining GDM processes.
Our project "Algorithms for Sustainable Group Decision Making" has concluded. In the course of this project we have published more than 35 papers and several open-source libraries.
We would like to express our thanks to everyone who contributed to this success, especially our many international collaborators! Thank you!
The book "Multi-Winner Voting with Approval Preferences" by Martin Lackner and Piotr Skowron has been published. It is an open access book and can be downloaded freely from Springer press.
The book includes an overview of major approval-based committee voting rules, an axiomatic analysis of these rules, a special focus on proportionality, algorithmic issues and related formalisms. We believe it can be helpful for both researchers entering the field as well as multi-winner veterans for looking up references.
We congratulate Jan for the “Dissertationspreis der Stadt Wien”, an annual award by the city council of Vienna. Details see here.
Jan Maly recently received a prestigious Erwin Schrödinger Fellowship. This fellowship will fund his research for the next 2.5 years. He will spend most of the time at the University of Amsterdam, working with Ulle Endriss and his team.
PI Martin Lackner and team member Jan Maly co-organized the First Vienna Workshop in Computational Social Choice, with talks form Christian Klamler, Martin Lackner, Jérôme Lang, Jiehua Chen and Thekla Hamm.
For more information see the website of the workshop.
We congratulate Jan to the successful defense of his PhD thesis Ranking Sets of Objects – How to Deal with Impossibility Results. Well done, Dr. Maly! :-)
The thesis was reviewed by Ulle Endriss (University of Amsterdam) and Jérôme Lang (CNRS, Paris), who formed the thesis committee together with Christian Klamler (Universität Graz) as national reviewer.
We are delighted to announce that three papers by team members have been accepted for presentation at the AAAI 2020 conference in New York.
Team members Martin Lackner and Jan Maly were able to attend the conference and present their work in oral presentations.
Jan Maly and Benjamin Krenn joined the project. Welcome!
The project "Algorithms for Sustainable Group Decision Making" started in Feburary 2019. Its projected duration is 3 years and 3 months.