Restricted Manipulation in Iterative Voting: Convergence and Condorcet Efficiency

Umberto Grandi
(University of Padova)
Andrea Loreggia
(University of Padova)
Francesca Rossi
(University of Padova)
Kristen Brent Venable
(Tulane University and IHMC)
Toby Walsh

In collective decision making, where a voting rule is used to take a collective decision among a group of agents, manipulation by one or more agents is usually considered negative behavior to be avoided, or at least to be made computationally difficult for the agents to perform. However, there are scenarios in which a restricted form of manipulation can instead be beneficial. In this paper we consider the iterative version of several voting rules, where at each step one agent is allowed to manipulate by modifying his ballot according to a set of restricted manipulation moves which are computationally easy and require little information to be performed. We prove convergence of iterative voting rules when restricted manipulation is allowed, and we present experiments showing that most iterative voting rules have a higher Condorcet efficiency than their non-iterative version.

In Fabio Mogavero, Aniello Murano and Moshe Y. Vardi: Proceedings 1st International Workshop on Strategic Reasoning (SR 2013), Rome, Italy, March 16-17, 2013, Electronic Proceedings in Theoretical Computer Science 112, pp. 17–24.
Published: 1st March 2013.

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