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False-name manipulations in weighted voting games

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Aziz, Haris, Bachrach, Yoram, Elkind, Edith and Paterson, Michael S. (2011) False-name manipulations in weighted voting games. Journal of Artificial Intelligence, Vol.40 . pp. 57-93. doi:10.1613/jair.3166 ISSN 1076-9757.

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Abstract

Weighted voting is a classic model of cooperation among agents in decision-making domains. In such games, each player has a weight, and a coalition of players wins the game if its total weight meets or exceeds a given quota. A player's power in such games is usually not directly proportional to his weight, and is measured by a power index, the most prominent among which are the Shapley-Shubik index and the Banzhaf index.

In this paper, we investigate by how much a player can change his power, as measured by the Shapley-Shubik index or the Banzhaf index, by means of a false-name manipulation, i.e., splitting his weight among two or more identities. For both indices, we provide upper and lower bounds on the effect of weight-splitting. We then show that checking whether a beneficial split exists is NP-hard, and discuss efficient algorithms for restricted cases of this problem, as well as randomized algorithms for the general case. We also provide an experimental evaluation of these algorithms.

Finally, we examine related forms of manipulative behavior, such as annexation, where a player subsumes other players, or merging, where several players unite into one. We characterize the computational complexity of such manipulations and provide limits on their effects. For the Banzhaf index, we describe a new paradox, which we term the Annexation Non-monotonicity Paradox.

Item Type: Journal Article
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Journal or Publication Title: Journal of Artificial Intelligence
Publisher: A N S I Network
ISSN: 1076-9757
Official Date: 2011
Dates:
DateEvent
2011Published
Volume: Vol.40
Page Range: pp. 57-93
DOI: 10.1613/jair.3166
Status: Peer Reviewed
Publication Status: Published

Data sourced from Thomson Reuters' Web of Knowledge

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