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A scheduling approach to coalitional manipulation

Published:07 June 2010Publication History

ABSTRACT

The coalitional manipulation problem is one of the central problems in computational social choice. In this paper, we focus on solving the problem under the important family of positional scoring rules, in an approximate sense that was advocated by Zuckerman et al. [SODA 2008, AIJ 2009]. Our main result is a polynomial-time algorithm with (roughly speaking) the following theoretical guarantee: given a manipulable instance with m alternatives, the algorithm finds a successful manipulation with at most m - 2 additional manipulators. Our technique is based on a reduction to the scheduling problem known as Q|pmtn|Cmax, along with a novel rounding procedure. We demonstrate that our analysis is tight by establishing a new type of integrality gap. We also resolve a known open question in computational social choice by showing that the coalitional manipulation problem remains (strongly) NP-complete for positional scoring rules even when votes are unweighted. Finally, we discuss the implications of our results with respect to the question: "Is there a prominent voting rule that is usually hard to manipulate?"

References

  1. John Bartholdi, III and James Orlin. Single transferable vote resists strategic voting. Social Choice and Welfare, 8(4):341--354, 1991.Google ScholarGoogle ScholarCross RefCross Ref
  2. John Bartholdi, III, Craig Tovey, and Michael Trick. The computational difficulty of manipulating an election. Social Choice and Welfare, 6(3):227--241, 1989.Google ScholarGoogle ScholarCross RefCross Ref
  3. Peter Brucker. Scheduling Algorithms. Springer Publishing Company, Incorporated, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Vincent Conitzer and Tuomas Sandholm. Universal voting protocol tweaks to make manipulation hard. In Proc. of IJCAI-03, pages 781--788, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Vincent Conitzer and Tuomas Sandholm. Nonexistence of voting rules that are usually hard to manipulate. In Proc. of AAAI-06, pages 627--634, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Vincent Conitzer, Tuomas Sandholm, and Jérôme Lang. When are elections with few candidates hard to manipulate? Journal of the ACM, 54(3):1--33, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Shahar Dobzinski and Ariel D. Procaccia. Frequent manipulability of elections: The case of two voters. In Proc. of WINE-08, pages 653--664, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Edith Elkind and Helger Lipmaa. Hybrid voting protocols and hardness of manipulation. In Proc. of ISAAC-05, pages 206--215, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Piotr Faliszewski, Edith Hemaspaandra, and Henning Schnoor. Copeland voting: ties matter. In Proc. of AAMAS-08, pages 983--990, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Ehud Friedgut, Gil Kalai, and Noam Nisan. Elections can be manipulated often. In Proc. of FOCS-08, pages 243--249, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Michael Garey and David Johnson. Computers and Intractability. W. H. Freeman and Company, 1979.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Allan Gibbard. Manipulation of voting schemes: a general result. Econometrica, 41:587--602, 1973.Google ScholarGoogle ScholarCross RefCross Ref
  13. Teofilo Gonzalez and Sartaj Sahni. Preemptive scheduling of uniform processor systems. J. ACM, 25(1):92--101, 1978. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Edith Hemaspaandra and Lane A. Hemaspaandra. Dichotomy for voting systems. Journal of Computer and System Sciences, 73(1):73--83, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Noam Nisan. Introduction to mechanism design (for computer scientists). In N. Nisan, T. Roughgarden, É. Tardos, and V. Vazirani, editors, Algorithmic Game Theory, chapter 9. Cambridge University Press, 2007.Google ScholarGoogle Scholar
  16. Michael L. Pinedo. Scheduling: Theory, Algorithms, and Systems. Springer, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ariel D. Procaccia and Jeffrey S. Rosenschein. Junta distributions and the average-case complexity of manipulating elections. Journal of Artificial Intelligence Research, 28:157--181, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Mark Satterthwaite. Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions. Journal of Economic Theory, 10:187--217, 1975.Google ScholarGoogle ScholarCross RefCross Ref
  19. Lirong Xia and Vincent Conitzer. Generalized scoring rules and the frequency of coalitional manipulability. In Proc. of EC-08, pages 109--118, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Lirong Xia and Vincent Conitzer. A sufficient condition for voting rules to be frequently manipulable. In Proc. of EC-08, pages 99--108, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Lirong Xia and Vincent Conitzer. Finite local consistency characterizes generalized scoring rules. In Proc. of IJCAI-09, pages 336--341, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Lirong Xia, Michael Zuckerman, Ariel D. Procaccia, Vincent Conitzer, and Jeffrey S. Rosenschein. Complexity of unweighted coalitional manipulation under some common voting rules. In Proc. of IJCAI-09, pages 348--353, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Michael Zuckerman, Ariel D. Procaccia, and Jeffrey S. Rosenschein. Algorithms for the coalitional manipulation problem. Artificial Intelligence, 173(2):392--412, 2009. Preliminary version in SODA-08. Google ScholarGoogle ScholarDigital LibraryDigital Library

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        cover image ACM Conferences
        EC '10: Proceedings of the 11th ACM conference on Electronic commerce
        June 2010
        400 pages
        ISBN:9781605588223
        DOI:10.1145/1807342

        Copyright © 2010 ACM

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        • Published: 7 June 2010

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