Handbook of Computational Social Choice
By Felix Brandt, Vincent Conitzer, U. Endriss, Jérôme Lang, Ariel D. Procaccia. 2016
984 citations recorded by the source corpus.
The rapidly growing field of computational social choice, at the intersection of computer science and economics, deals with the computational aspects of collective decision making. This handbook, written by thirty-six prominent members of the computational social choice community, covers the field comprehensively. Chapters devoted to each of the field's major themes offer detailed introductions. Topics include voting theory (such as the computational complexity of winner determination and manipulation in elections), fair allocation (such as algorithms for dividing divisible and indivisible goods), coalition formation (such as matching and hedonic games), and many more. Graduate students, researchers, and professionals in computer science, economics, mathematics, political science, and philosophy will benefit from this accessible and self-contained book.
Subfields: Artificial Intelligence, Economics and Econometrics, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/536145435bf6841dd689e7c28e7d1954b0fe1ec5
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Lingxiao Huang
- L. Elisa Celis
- Nisheeth K. Vishnoi
- Iyad Rahwan
- Tim Roughgarden
- Seth D. Baum
- Jonathan Ullman
- Aaron Roth
In Economics and Econometrics
In Management Science and Operations Research
- Nisheeth K. Vishnoi
- Lingxiao Huang
- L. Elisa Celis
- Iyad Rahwan
- Tim Roughgarden
- Seth D. Baum
- Benjamin Plaut
- É. Tardos
Citations in the corpus
- Multiwinner Voting with Fairness Constraints (2017, background): “As the fairness constraints restrict the set of feasible committees in the same way for any set of voters, the argument for consistency remains the same (see [22, Theorem 7]).”
- Social choice ethics in artificial intelligence (2017, background): “There is a more extensive study of ‘‘computational social choice’’ relating aspects of social choice theory and computer science (Brandt et al. 2015).”
- Society-in-the-loop: programming the algorithmic social contract (2017, background): “The field of computational social choice [4, 50] explores the aggregation of societal preferences and fair allocation of resources.”
- Almost Envy-Freeness with General Valuations (2017, background): “Many different notions of fairness have been studied, with envy-freeness being one of the most prominent (see e.g., [Brams and Taylor, 1996, Brandt et al., 2016, Moulin, 2003] for further background).”