Junta distributions and the average-case complexity of manipulating elections

Journal of Artificial Intelligence Research

Volumn 28, Issue , 2007, Pages 157-181

  Procaccia, Ariel D ^a   Rosenschein, Jeffrey S ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; NETWORK PROTOCOLS; SOCIAL ASPECTS;

JUNTA DISTRIBUTIONS; WORST-CASE ANALYSIS;

ARTIFICIAL INTELLIGENCE;

EID: 34249029918     PISSN: None     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.2148     Document Type: Article

References (21)

1. Alon, N., & Spencer, J. H. (1992). The Probabilistic Method. Wiley and Sons.
2. Bachrach, Y., & Rosenschein, J. S. (2006). Achieving allocatively-efficient and strongly budget-balanced mechanisms in the network flow domain for bounded-rational agents. In The Seventh International Workshop on Agent-Mediated Electronic Commerce: Designing Mechanisms and Systems, Utrecht, The Netherlands (AMEC 2005), No. 3937 in Lecture Notes in Artificial Intelligence, pp. 71-84. Springer-Verlag, Berlin.
3. Bartholdi, J., & Orlin, J. (1991). Single transferable vote resists strategic voting. Social Choice and Welfare, 8, 341-354.
4. Bartholdi, J., Tovey, C. A., & Trick, M. A. (1989a). The computational difficulty of manipulating an election. Social Choice and Welfare, 6, 227-241.
5. Bartholdi, J., Tovey, C. A., & Trick, M. A. (1989b). Voting schemes for which it can be difficult to tell who who the election. Social Choice and Welfare, 6, 157-165.
6. Bartholdi, J., Tovey, C. A., & Trick, M. A. (1992). How hard is it to control an election. Mathematical and Computer Modelling, 16, 27-40.
7. Conitzer, V., Lang, J., &: Sandholm, T. (2003). How many candidates are needed to make elections hard to manipulate?. In Proceedings of the International Conference on 'Theoretical Aspects of Reasoning about Knowledge, pp. 201-214.
8. Conitzer, V., & Sandholm, T. (2002). Complexity of manipulating elections with few candidates. In Proceedings of the National Conference on Artificial Intelligence, pp. 314-319.
9. Conitzer, V., & Sandholm, T. (2003). Universal voting protocol tweaks to make manipulation hard. In Proceedings of the International Joint Conference on Artificial Intelligence, pp. 781-788.
10. Conitzer, V., & Sandholm, T. (2006). Nonexistence of voting rules that are usually hard to manipulate. In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 627-634.
11. Elkind, E., & Lipmaa, H. (2005a). Hybrid voting protocols and hardness of manipulation. In 16th Annual International Symposium on Algorithms and Computation, Lecture Notes in Computer Science, pp. 206-215. Springer-Verlag.
12. Elkind, E., & Lipmaa, H. (2005b). Small coalitions cannot manipulate voting. In International Conference on Financial Cryptography, Lecture Notes in Computer Science. Springer-Verlag.
13. Ephrati, E., & Rosenschein, J. S. (1997). A heuristic technique for multiagent planning. Annals of Mathematics and Artificial Intelligence, 20, 13-67.
14. Feller, W. (1968). Introduction to Probability Theory and its Applications (3rd edition)., Vol. 1, p. 254. John Wiley.
15. Ghosh, S., Mundhe, M., Hernandez, K., & Sen, S. (1999). Voting for movies: the anatomy of a recommender system. In Proceedings of the Third Annual Conference on Autonomous Agents, pp. 434-435.
16. Gibbard, A. (1973). Manipulation of voting schemes. Econometrica, 41, 587-602.
17. Haynes, T., Sen, S., Arora, N., & Nadella, R. (1997). An automated meeting scheduling system that utilizes user preferences. In Proceedings of the First International Conference on Autonomous Agents, pp. 308-315.
18. Hemaspaandra, E., & Hemaspaandra, L. A. (2005). Dichotomy for voting systems. University of Rochester Department of Computer Science Technical Report 861.
19. Procaccia, A. D., Rosenschein, J. S., & Zohar, A. (2007). Multi-winner elections: Complexity of manipulation, control and winner-determination. In The Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007), Hyderabad, India. To appear.
20. Satterthwaite, M. (1975). Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions. Journal of Economic Theory, 10, 187-217.
21. Trevisan, L. (2002). Lecture notes on computational complexity. Available from http://www.cs.berkeley.edu/~luca/notes/complexitynotes02.pdf. Lecture 12.