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Parameterization in Computational Social Choice

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  • First Online:
Encyclopedia of Algorithms

Years and Authors of Summarized Original Work

  • 1989; Bartholdi, Tovey, Trick

  • 2009; Betzler, Uhlmann

  • 2011; Liu, Feng, Zhu, Luan

  • 2012; Dorn, Schlotter

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)?

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Recommended Reading

  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):157–165

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  2. Bartholdi JJ III, Tovey CA, Trick MA (1992) How hard is it to control an election? Math Comput Model 16(8/9):27–40

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  3. Betzler N, Uhlmann J (2009) Parameterized complexity of candidate control in elections and related digraph problems. Theor Comput Sci 410(52):43–53

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  4. Betzler N, Guo J, Niedermeier R (2010) Parameterized computational complexity of Dodgson and Young elections. Inf Comput 208(2):165–177

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  5. 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 318–363

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  6. 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):358–373

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  7. 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 1398–1404

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  8. Dorn B, Schlotter I (2012) Multivariate complexity analysis of swap bribery. Algorithmica 64(1):126–151

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  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 299–310

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  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):2746–2753

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Author information

Authors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Piotr Faliszewski

  2. Department of Mathematics and Computer Science, University of Jena, Jena, Germany

    Rolf Niedermeier

  3. Institut für Softwaretechnik und Theoretische Informatik, Technische Universität Berlin, Ernst-Reuter-Platz 7, D-10587, Berlin, Germany

    Rolf Niedermeier

Authors
  1. Piotr Faliszewski
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  2. Rolf Niedermeier
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Corresponding author

Correspondence to Piotr Faliszewski .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA

    Ming-Yang Kao

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Faliszewski, P., Niedermeier, R. (2016). Parameterization in Computational Social Choice. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_785

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