Advertisement

Review of Economic Design

, Volume 11, Issue 3, pp 217–224 | Cite as

On complexity of lobbying in multiple referenda

  • Robin Christian
  • Mike Fellows
  • Frances Rosamond
  • Arkadii Slinko
Original Paper

Abstract

In this paper we show that lobbying in conditions of “direct democracy” is virtually impossible, even in conditions of complete information about voters’ preferences, since it would require solving a very computationally hard problem. We use the apparatus of parametrized complexity for this purpose.

Keywords

Lobbying Referendum Parametrized complexity 

JEL Classification Numbers

D72 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bartholdi JJ III, Orlin JB (1991) Single transferable vote resists strategic voting. Soc Choice Welfare 8:341–354Google Scholar
  2. Bartholdi JJ III, Tovey CA, Trick MA (1989a) Voting schemes for which it may be difficult to tell who won the election. Soc Choice Welfare 6:157–165CrossRefGoogle Scholar
  3. Bartholdi JJ III, Tovey CA, Trick MA (1989b) The computational difficulty of manipulating an election. Soc Choice Welfare 6:227–241CrossRefGoogle Scholar
  4. Bartholdi JJ III, Narasimhan LS, Tovey CA (1991) Recognizing majority rule equilibrium in spatial voting. Soc Choice Welfare 8:183–197Google Scholar
  5. Bartholdi JJ III, Tovey CA, Trick MA (1992) How hard is to control an election? Math Comput Model 16(8/9):27–40CrossRefGoogle Scholar
  6. Christian R, Fellows M, Rosamond F, Slinko A (2006) On complexity of lobbying in multiple referenda. In: Endriss U, Lang J (eds) Proceedings of the 1st international workshop on computational social choice (COMSOC–2006), pp 87–96. Universiteit van Amsterdam, AmsterdamGoogle Scholar
  7. Conitzer V, Sandholm T (2002) Complexity of manipulating elections with few candidates. In: Proceedings of the national conference on artificial intelligence (AAAI), Edmonton, Canada (to appear) available at http://www.cs.cmu.edu/ sandholmGoogle Scholar
  8. Diffe W, Hellman M (1976) New directions in cryptography. IEEE Trans Inform Theory IT–22:644–654CrossRefGoogle Scholar
  9. Downey RG, Fellows MR (1999) Parametrized complexity. Springer, New YorkGoogle Scholar
  10. Dwork C, Kumar R, Naor M, Sivakumar D (2001) Rank aggregation methods for the web. WWW, pp 613–622Google Scholar
  11. Ephrati E (1994) A non-manipulable meeting scheduling system. In: Proceedings 13th international distributed artificial intelligence workshop, Lake Quinalt, Washington, July, AAAI Press Technical Report WS-94-02Google Scholar
  12. Ephrati E, Rosenschein J (1991) The Clarke tax as a consensus mechanism among automated agents. In: Proceedings of the national conference on artificial intelligence (AAAI). Anaheim, CA, pp 173–178Google Scholar
  13. Ephrati E, Rosenschein J (1993) Multi-agent planning as a dynamic search for social consensus. In: Proceedings 13th international joint conference on artificial intelligence (IJCAI). Chambery, France, pp 423–429Google Scholar
  14. Faliszewski P, Hemaspaandra E, Hemaspaandra L, Rothe J (2006) A richer understanding of the complexity of election systems. Available at http://www.arxiv.org/abs/cs.GT/0609112Google Scholar
  15. Garey M, Johnson D (1979) Computers and intractability: a guide to the theory of NP-completeness. Freeman, San FranciscoGoogle Scholar
  16. Hemaspaandra E, Hemaspaandra L (2000) Computational politics: electoral systems. In: Proceedings of the 25th international symposium on mathematical foundations of computer science. Springer-Verlag lecture notes in computer science #1893, August/September, pp 64–83Google Scholar
  17. Hemaspaandra E, Hemaspaandra L, Rothe J (1997) Exact analysis of Dodgson elections: Lewis Carroll’s 1876 voting system is complete for parallel access to NP. J ACM 44(6):806–825CrossRefGoogle Scholar
  18. Hemaspaandra E, Spakovski H, Vogel J (2005) The complexity of Kemeny elections. Theor Comput Sci 349(3):383–391Google Scholar
  19. McCabe-Dansted J (2006) Approximability and computational feasibility of Dodgson’s rule. Master’s thesis. The University of Auckland, AucklandGoogle Scholar
  20. Phillips K (1994) Arrogant capital. Little Brown and Company, BostonGoogle Scholar
  21. Rothe J, Spakovski H, Vogel J (2003) Exact complexity of the winner problem for Young elections. Theory Comput Syst 36(4):375–386CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Robin Christian
    • 1
  • Mike Fellows
    • 2
  • Frances Rosamond
    • 2
  • Arkadii Slinko
    • 3
  1. 1.Department of Combinatorics and OptimizationUniversity of WaterlooWaterlooCanada
  2. 2.Parameterized Complexity Research UnitUniversity of NewcastleNewcastleAustralia
  3. 3.Department of MathematicsUniversity of AucklandAucklandNew Zealand

Personalised recommendations