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In the late 19th century, Lars Edvard Phragmén proposed a load-balancing approach for selecting committees based on approval ballots. We consider three committee voting rules resulting from this approach: two optimization variants—one minimizing the maximal load and one minimizing the variance of loads—and a sequential variant. We study Phragmén's methods(More)
Runoff voting rules such as single transferable vote (STV) and Baldwin's rule are of particular interest in computational social choice due to their recursive nature and hardness of manipulation, as well as in (human) practice because they are relatively easy to understand. However, they are not known for their compliance with desirable axiomatic properties(More)
Algorithms for solving Stackelberg games are used in an ever-growing variety of real-world domains. Previous work has extended this framework to allow the leader to commit not only to a distribution over actions, but also to a scheme for stochastically signaling information about these actions to the follower. This can result in higher utility for the(More)
In (computational) social choice, how ties are broken can affect the axiomatic and computational properties of a voting rule. In this paper, we first consider settings where we may have multiple winners. We formalize the notion of parallel universes tiebreaking with respect to a particular tree that represents the computation of the winners, and show that(More)
In many multiagent environments, a designer has some, but limited control over the game being played. In this paper, we formalize this by considering incompletely specified games, in which some entries of the payoff matrices can be chosen from a specified set. We show that it is NP-hard for the designer to make this choices optimally, even in zero-sum(More)
A prediction market is a useful means of aggregating information about a future event. To function, the market needs a trusted entity who will verify the true outcome in the end. Motivated by the recent introduction of decentralized prediction markets, we introduce a mechanism that allows for the outcome to be determined by the votes of a group of arbiters(More)
We study the problem of finding a recommendation for an un-informed user in a social network by weighting and aggregating the opinions offered by the informed users in the network. In social networks, an informed user may try to manipulate the recommendation by performing a false-name manipulation, wherein the user submits multiple opinions through fake(More)