http://www.dagstuhl.de/17261

June 25 – 30 , 2017, Dagstuhl Seminar 17261

Voting: Beyond Simple Majorities and Single-Winner Elections

Organizers

Dorothea Baumeister (Heinrich-Heine-Universität Düsseldorf, DE)
Piotr Faliszewski (AGH University of Science & Technology – Krakow, PL)
Annick Laruelle (University of the Basque Country – Bilbao, ES)
Toby Walsh (TU Berlin, DE)

For support, please contact

Annette Beyer for administrative matters

Michael Gerke for scientific matters

Dagstuhl Reports

As part of the mandatory documentation, participants are asked to submit their talk abstracts, working group results, etc. for publication in our series Dagstuhl Reports via the Dagstuhl Reports Submission System.

Documents

List of Participants
Shared Documents
Dagstuhl Seminar Wiki
Dagstuhl Seminar Schedule [pdf]

(Use seminar number and access code to log in)

Press Room

Motivation

Computational social choice is an interdisciplinary field of research, focused on computational and algorithmic issues pertaining to aggregating preferences of agents—perhaps self-interested and strategic—and providing them with joint decisions. Computational social choice combines the tools and approaches of social choice theory, computer science (with particular focus on artificial intelligence and theoretical computer science), economics, and operations research. The distinctive feature of computational social choice—as opposed to the classic social choice theory— is that computational considerations (e.g., efficiency of computing outcomes of the preference aggregation processes) are given significant attention. Nonetheless, the two research areas are deeply connected and there is significant interaction between them. The best studied model of (computational) social choice regards single-winner elections. Agents (voters) express their preferences regarding the available candidates (often in the form of rankings, from the most to the least desirable candidate) and then a voting rule (i.e., an appropriate algorithm) specifies the election winner. Due to the fantastic progress in social choice (over the last half a century) and in computational social choice (over the last fifteen years or so), essentially all the stages of the above-described process are quite well studied. However, in the modern world—especially in the era of ubiquitous use of social media—it appears that there is a great range of preference aggregation settings where the classic approach falls short.

The goal of this seminar is to discuss:


  1. multi-winner elections: parliamentary elections are perhaps the most archetypal example of a multi-winner election, but there are applications far beyond the world of politics.
  2. multi-issue elections: decisions on a sequence of interdependent issues.
  3. elections where voters express their preferences in various non-standard ways (ranging from extensions of dichotomous preferences to complex languages allowing one to express condi- tional statements).
  4. other voting-related settings, including peer selection, and judgement aggregation.

Although voting theory is usually associated with political elections, its possible applications are found in all aspects of collective decision making. Applications in computer science include webpage ranking, online recommendation systems for products and services, and various scheduling tools (such as, e.g., Doodle). Further, there are relevant applications of (multi-winner) voting in the industry (for example finding the best set of products for a given group of clients). A consequence of this diversity of applications is the interdisciplinary approach of the seminar. We intend the seminar to be a place where researchers from various areas of research (including computer science, economics, political science, etc.) can exchange their views, ideas, and experiences regarding these new preference aggregation problems.

This seminar is related to four previous seminars on Computational Social Choice (2007, 2010, 2012, 2015), which contributed to the development of the community.

License
  Creative Commons BY 3.0 DE
  Dorothea Baumeister and Piotr Faliszewski and Annick Laruelle and Toby Walsh

Dagstuhl Seminar Series

Classification

  • Artificial Intelligence / Robotics
  • Data Structures / Algorithms / Complexity
  • Modelling / Simulation

Keywords

  • Social Choice
  • Artificial Intelligence
  • Multi Agent Systems
  • Collective Decision Making
  • Voting
  • Preference Aggregation
  • Preference Elicitation and Preference Learning

Book exhibition

Books from the participants of the current Seminar 

Book exhibition in the library, ground floor, during the seminar week.

Documentation

In the series Dagstuhl Reports each Dagstuhl Seminar and Dagstuhl Perspectives Workshop is documented. The seminar organizers, in cooperation with the collector, prepare a report that includes contributions from the participants' talks together with a summary of the seminar.

 

Download overview leaflet (PDF).

Publications

Furthermore, a comprehensive peer-reviewed collection of research papers can be published in the series Dagstuhl Follow-Ups.

Dagstuhl's Impact

Please inform us when a publication was published as a result from your seminar. These publications are listed in the category Dagstuhl's Impact and are presented on a special shelf on the ground floor of the library.