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Efficient algorithm for designing weighted voting games

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Aziz, Haris, Paterson, Mike and Leech, Dennis (2007) Efficient algorithm for designing weighted voting games. In: 11th IEEE International Multitopic Conference, Lahore, PAKISTAN, DEC 28-30, 2007. Published in: INMIC 2007: PROCEEDINGS OF THE 11TH IEEE INTERNATIONAL MULTITOPIC CONFERENCE pp. 211-216.

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Abstract

Weighted voting games are mathematical models used to analyse situations where voters with variable voting weight vote in favour of or against a decision. They have been applied in various political and economic organizations. Similar combinatorial models are also encountered in neuroscience, threshold logic, reliability theory and distributed systems. The calculation of voting powers of players in a weighted voting game has been extensively researched in the last few years. However, the inverse problem of designing a weighted voting game with a desirable distribution of power has received less attention. We present an elegant algorithm which uses generating functions and interpolation to compute an integer weight vector for target Banzhaf power indices. This algorithm has better performance than any other known to us. It can also be used to design egalitarian two-tier weighted voting games and a representative weighted voting game for a multiple weighted voting game.

Item Type: Conference Item (UNSPECIFIED)
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Journal or Publication Title: INMIC 2007: PROCEEDINGS OF THE 11TH IEEE INTERNATIONAL MULTITOPIC CONFERENCE
Publisher: IEEE
ISBN: 978-1-4244-1552-6
Date: 2007
Number of Pages: 6
Page Range: pp. 211-216
Identification Number: 10.1109/INMIC.2007.4557718
Publication Status: Published
Title of Event: 11th IEEE International Multitopic Conference
Location of Event: Lahore, PAKISTAN
Date(s) of Event: DEC 28-30, 2007
URI: http://wrap.warwick.ac.uk/id/eprint/29816

Data sourced from Thomson Reuters' Web of Knowledge

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