Skip to main content
Log in

On the computational complexity of weighted voting games

  • Published:
Annals of Mathematics and Artificial Intelligence Aims and scope Submit manuscript

Abstract

Coalitional games provide a useful tool for modeling cooperation in multiagent systems. An important special class of coalitional games is weighted voting games, in which each player has a weight (intuitively corresponding to its contribution), and a coalition is successful if the sum of its members’ weights meets or exceeds a given threshold. A key question in coalitional games is finding coalitions and payoff division schemes that are stable, i.e., no group of players has any rational incentive to leave. In this paper, we investigate the computational complexity of stability-related questions for weighted voting games. We study problems involving the core, the least core, and the nucleolus, distinguishing those that are polynomial-time computable from those that are NP-hard or coNP-hard, and providing pseudopolynomial and approximation algorithms for some of the computationally hard problems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Ausiello, G., Crescenzi, P., Gambosi, G., Kann, V., Marchetti-Spaccamela, A., Protasi, M.: Complexity and Approximation. Springer, Berlin (1999)

    MATH  Google Scholar 

  2. Banzhaf, J.F.: Weighted voting doesn’t work: a mathematical analysis. Rutgers Law Rev. 19, 317–343 (1965)

    Google Scholar 

  3. Bilbao, J., Fernández, J., López, J.: Complexity in cooperative game theory (manuscript)

  4. Bilbao, J.M., Fernández, J.R., Jiminéz, N., López, J.J.: Voting power in the European union enlargement. Eur. J. Oper. Res. 143, 181–196 (2002)

    Article  MATH  Google Scholar 

  5. Conitzer, V., Sandholm, T.: Computing Shapley values, manipulating value division schemes, and checking core membership in multi-issue domains. In: Proceedings of the Ninteenth National Conference on Artificial Intelligence (AAAI-2004), pp. 219–225, San Jose, CA (2004)

  6. Conitzer, V., Sandholm, T.: Complexity of constructing solutions in the core based on synergies among coalitions. Artif. Intell. 170, 607–619 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  7. Deng, X., Fang, Q., Sun, X.: Finding nucleolus of flow game. In: Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 124–131. ACM, New York (2006)

    Chapter  Google Scholar 

  8. Deng, X., Papadimitriou, C.H.: On the complexity of cooperative solution concepts. Math. Oper. Res. 19(2), 257–266 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  9. Elkind, E., Chalkiadakis, G., Jennings, N.R.: Coalition structures in weighted voting games. In: Proc. 18th European Conference on Artificial Intelligence (ECAI’08) (2008)

  10. Elkind, E., Goldberg, L.A., Goldberg, P.W., Wooldridge, M.: Computational complexity of weighted threshold games. In: Proc. 22nd Conference on Artificial Intelligence (AAAI’07) (2007)

  11. Elkind, E., Goldberg, L.A., Goldberg, P.W., Wooldridge, M.: On the dimensionality of voting games. In: Proc. 23rd Conference on Artificial Intelligence (AAAI’08) (2008)

  12. Elkind, E., Pasechnik, D.: Computing the nucleolus of weighted voting games. In: Proc. 20th ACM-SIAM Symposium on Discrete Algorithms (SODA’09) (2009)

  13. Garey, M.R., Johnson, D.S.: Computers and Intractability; A Guide to the Theory of NP-Completeness. W.H. Freeman, New York (1990)

    Google Scholar 

  14. Grötschel, M., Lovász, L., Schrijver, A.: Geometric Algorithms and Combinatorial Optimization, Algorithms and Combinatorics, vol. 2, 2nd edn. Springer, Berlin (1993)

    Google Scholar 

  15. Ieong, S., Shoham, Y.: Marginal contribution nets: a compact representation scheme for coalitional games. In: Proceedings of the Sixth ACM Conference on Electronic Commerce (EC’05), Vancouver, Canada (2005)

  16. Matsui, T., Matsui, Y.: A survey of algorithms for calculating power indices of weighted majority games. J. Oper. Res. Soc. Jpn 43(1), 71–86 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  17. Matsui, Y., Matsui, T.: NP-completeness for calculating power indices of weighted majority games. Theor. Comp. Sci. 263(1–2), 305–310 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  18. Osborne, M.J., Rubinstein, A.: A Course in Game Theory. MIT, Cambridge (1994)

    Google Scholar 

  19. Papadimitriou, C.H.: Computational Complexity. Addison-Wesley, Reading (1994)

    MATH  Google Scholar 

  20. Peleg, B.: On weights of constant-sum majority games. SIAM J. Appl. Math. 16, 527–532 (1968)

    Article  MATH  MathSciNet  Google Scholar 

  21. Prasad, K., Kelly, J.S.: NP-completeness of some problems concerning voting games. Int. J. Game Theory 19(1), 1–9 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  22. Sandholm, T., Larson, K., Andersson, M., Shehory, O., Tohmé, F.: Coalition structure generation with worst case guarantees. Artif. Intell. 111(1–2), 209–238 (1999)

    Article  MATH  Google Scholar 

  23. Schmeidler, D.: The nucleolus of a characteristic function game. SIAM J. Appl. Math. 17, 1163–1170 (1969)

    Article  MATH  MathSciNet  Google Scholar 

  24. Schrijver, A.: Combinatorial Optimization: Polyhedra and Efficiency. Springer, New York (2003)

    MATH  Google Scholar 

  25. Shehory, O., Kraus, S.: Coalition formation among autonomous agents: strategies and complexity. In: Castelfranchim, C., Müller, J.-P. (eds.) From Reaction to Cognition—Fifth European Workshop on Modelling Autonomous Agents in a Multi-Agent World, MAAMAW-93. LNAI, vol. 957, pp. 56–72. Springer, Berlin (1995)

    Google Scholar 

  26. Shehory, O., Kraus, S.: Task allocation via coalition formation among autonomous agents. In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95), pp. 655–661, Montréal, Québec, Canada (1995)

  27. Shehory, O., Kraus, S.: Methods for task allocation via agent coalition formation. Artif. Intell. 101(1–2), 165–200 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  28. Taylor, A., Zwicker, W.: Weighted voting, multicameral representation, and power. Games Econom. Behav. 5, 170–181 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  29. Taylor, A.D., Zwicker, W.S.: Simple Games: Desirability Relations, Trading, Pseudoweightings. Princeton University Press, Princeton (1999)

    MATH  Google Scholar 

  30. Wolsey, L.A.: The nucleolus and kernel for simple games or special valid inequalities for 0 − 1 linear integer programs. Int. J. Game Theory 5(4), 227–238 (1976)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Edith Elkind.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Elkind, E., Goldberg, L.A., Goldberg, P.W. et al. On the computational complexity of weighted voting games. Ann Math Artif Intell 56, 109–131 (2009). https://doi.org/10.1007/s10472-009-9162-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10472-009-9162-5

Keywords

Mathematics Subject Classification (2000)

Navigation