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Worst-case Bounds on Power vs. Proportion in Weighted Voting Games with an Application to False-name Manipulation

Published: 04 January 2022 Publication History

Abstract

Weighted voting games apply to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs. small players in these games. We model small (big) players as having single (multiple) votes. The aggregate relative power of big players is measured w.r.t. their votes proportion. For this ratio, we show small constant worst-case bounds for the Shapley-Shubik and the Deegan-Packel indices. In sharp contrast, this ratio is unbounded for the Banzhaf index. As an application, we define a false-name strategic normal form game where each big player may split its votes between false identities, and study its various properties. Together, our results provide foundations for the implications of players’ size, modeled as their ability to split, on their relative power.

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Published In

cover image Journal of Artificial Intelligence Research
Journal of Artificial Intelligence Research  Volume 72, Issue
Jan 2022
1485 pages

Publisher

AI Access Foundation

El Segundo, CA, United States

Publication History

Published: 04 January 2022
Published in JAIR Volume 72

Author Tags

  1. autonomous agents
  2. game theory
  3. decision theory
  4. mathematical foundations

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