A Short Introduction to Computational Social Choice

By Yann Chevaleyre, U. Endriss, Jérôme Lang, N. Maudet. 2007

307 citations recorded by the source corpus.

Computational social choice is an interdisciplinary field of study at the interface of social choice theory and computer science, promoting an exchange of ideas in both directions. On the one hand, it is concerned with the application of techniques developed in computer science, such as complexity analysis or algorithm design, to the study of social choice mechanisms, such as voting procedures or fair division algorithms. On the other hand, computational social choice is concerned with importing concepts from social choice theory into computing. For instance, the study of preference aggregation mechanisms is also very relevant to multiagent systems. In this short paper we give a general introduction to computational social choice, by proposing a taxonomy of the issues addressed by this discipline, together with some illustrative examples and an (incomplete) bibliography.

Subfields: Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research

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Citations in the corpus

Explanation in Artificial Intelligence: Insights from the Social Sciences (2017, background): “4) is important for those working in collective intelligence; areas such as in multi-agent planning [11], computational social choice [26], or argumentation [8].”
Knowledge-based Systems (2009, unknown): “This problem is the core of disciplines such as social choice (e.g., [47,48]), multi-expert decision-making (e.g., [49,50]), or group decision-making (e.g., [51–54]).”
Preference-based Online Learning with Dueling Bandits: A Survey (2018, background): “This is exactly the challenge faced by ranking procedures , which have been studied quite intensely in operations research and decision theory (Moulin, 1988; Chevaleyre et al., 2007).”
Algorithmics of Matching Under Preferences (2013, background): “Computational social choice theory [150] addresses computational challenges arising in situations where multiple agents must reach a collective”
Generic Exploration and K-armed Voting Bandits (2013, methodology): “If we change the election criterion according to the vast social choice theory (see Chevaleyre et al., 2007, for a survey),we can decline the dueling bandits in several unexplored flavors: for instance Borda bandits, Copeland bandits, Slater bandits, or Kemeny bandits.”
A Survey of Preference-Based Online Learning with Bandit Algorithms (2014, background): “This is exactly the challenge faced by ranking procedures, which have been studied quite intensely in operations research and decision theory [40, 18].”