Encyclopedia of Algorithms

Living Edition
| Editors: Ming-Yang Kao

Parameterization in Computational Social Choice

Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27848-8_785-1

Years and Authors of Summarized Original Work

  • 1989; Bartholdi, Tovey, Trick

  • 2009; Betzler, Uhlmann

  • 2012; Dorn, Schlotter

  • 2011; Liu, Feng, Zhu, Luan

Problem Definition

Computational Social Choice is an interdisciplinary research area involving Economics, Political Science, and Social Science on the one side and Mathematics and Computer Science (including artificial intelligence and multi-agent systems) on the other side. Concrete questions addressed in this area include the following three: How efficiently can one determine the winner of an election, given a number of votes with preferences over a number of alternatives? Is it possible to obtain a desirable outcome of an election by executing a number of campaigning actions? (Formally, such problems are often modeled as bribery.) Can the chair of an election influence the result of an election by modifying the set of available alternatives (e.g., by encouraging some alternatives (candidates) to participate in the run)?

The main...


NP-hard problems Parameterized and multivariate complexity analysis Voting problems Winner determination Bribery in elections Control in elections 
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Recommended Reading

  1. 1.
    Bartholdi JJ III, Tovey CA, Trick MA (1989) Voting schemes for which it can be difficult to tell who won the election. Soc Choice Welf 6(2):157–165MathSciNetCrossRefMATHGoogle Scholar
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    Bartholdi JJ III, Tovey CA, Trick MA (1992) How hard is it to control an election? Math Comput Model 16(8/9):27–40MathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Betzler N, Uhlmann J (2009) Parameterized complexity of candidate control in elections and related digraph problems. Theor Comput Sci 410(52):43–53MathSciNetCrossRefGoogle Scholar
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    Betzler N, Guo J, Niedermeier R (2010) Parameterized computational complexity of Dodgson and Young elections. Inf Comput 208(2):165–177MathSciNetCrossRefMATHGoogle Scholar
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    Betzler N, Bredereck R, Chen J, Niedermeier R (2012) Studies in computational aspects of voting – a parameterized complexity perspective. In: Bodlaender HL, Downey R, Fomin FV, Marx D (eds) The multivariate algorithmic revolution and beyond. LNCS, vol 7370. Springer, Berlin/New York, pp 318–363CrossRefGoogle Scholar
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    Bredereck R, Chen J, Faliszewski P, Guo J, Niedermeier R, Woeginger GJ (2014) Parameterized algorithmics for computational social choice: nine research challenges. Tsinghua Sci Technol 19(4):358–373MathSciNetCrossRefGoogle Scholar
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    Bredereck R, Chen J, Nichterlein A, Faliszewski P, Niedermeier R (2014) Prices matter for the parameterized complexity of shift bribery. In: Proceedings of the 28th Conference on Artificial Intelligence (AAAI’14), Quebéc City, pp 1398–1404Google Scholar
  8. 8.
    Dorn B, Schlotter I (2012) Multivariate complexity analysis of swap bribery. Algorithmica 64(1):126–151MathSciNetCrossRefMATHGoogle Scholar
  9. 9.
    Elkind E, Faliszewski P, Slinko A (2009) Swap bribery. In: Proceedings of the 2nd International Symposium on Algorithmic Game Theory (SAGT ’09). LNCS, vol 5814. Springer, Berlin/Heidelberg, pp 299–310Google Scholar
  10. 10.
    Liu H, Feng H, Zhu D, Luan J (2009) Parameterized computational complexity of control problems in voting systems. Theor Comput Sci 410(27–29):2746–2753MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakowPoland
  2. 2.Institut für Softwaretechnik und Theoretische InformatikTU BerlinBerlinGermany