14 research outputs found

    Are weighted games sufficiently good for binary voting?

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    A note on the growth of the dimension in complete simple games

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    A note on the growth of the dimension in complete simple games

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    The remoteness from a simple game to a weighted game can be measured by the concept of the dimension or the more general Boolean dimension. It is known that both notions can be exponential in the number of voters. For complete simple games it was only recently shown that the dimension can also be exponential. Here we show that this is also the case for complete simple games with two types of voters and for the Boolean dimension of general complete simple games, which was posed as an open problem.Comment: 9 page

    Dimension of the Lisbon voting rules in the EU Council : a challenge and new world record

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    The new voting system of the Council of the European Union cannot be represented as the intersection of six or fewer weighted games, i.e., its dimension is at least 7. This sets a new record for real-world voting bodies. A heuristic combination of different discrete optimization methods yields a representation as the intersection of 13368 weighted games. Determination of the exact dimension is posed as a challenge to the community. The system's Boolean dimension is proven to be 3.Comment: 8 pages, 1 figure; Incorrect losing coalitions were reported in the published version: S. Kurz and S. Napel (2016). Dimension of the Lisbon voting rules in the EU Council: a challenge and new world record. Optimization Letters, 10(6), 1245-1256, doi:10.1007/s11590-015-0917-0, due to a labeling inconsistency. The authors thank J\"org Aldag and Werner Kirsch for pointing out this erro

    On the Construction of High Dimensional Simple Games

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    Voting is a commonly applied method for the aggregation of the preferences of multiple agents into a joint decision. If preferences are binary, i.e., "yes" and "no", every voting system can be described by a (monotone) Boolean function χ ⁣:{0,1}n{0,1}\chi\colon\{0,1\}^n\rightarrow \{0,1\}. However, its naive encoding needs 2n2^n bits. The subclass of threshold functions, which is sufficient for homogeneous agents, allows a more succinct representation using nn weights and one threshold. For heterogeneous agents, one can represent χ\chi as an intersection of kk threshold functions. Taylor and Zwicker have constructed a sequence of examples requiring k2n21k\ge 2^{\frac{n}{2}-1} and provided a construction guaranteeing k(nn/2)2no(n)k\le {n\choose {\lfloor n/2\rfloor}}\in 2^{n-o(n)}. The magnitude of the worst-case situation was thought to be determined by Elkind et al.~in 2008, but the analysis unfortunately turned out to be wrong. Here we uncover a relation to coding theory that allows the determination of the minimum number kk for a subclass of voting systems. As an application, we give a construction for k2no(n)k\ge 2^{n-o(n)}, i.e., there is no gain from a representation complexity point of view.Comment: 13 pages, 1 tabl

    Cooperation through social influence

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    We consider a simple and altruistic multiagent system in which the agents are eager to perform a collective task but where their real engagement depends on the willingness to perform the task of other influential agents. We model this scenario by an influence game, a cooperative simple game in which a team (or coalition) of players succeeds if it is able to convince enough agents to participate in the task (to vote in favor of a decision). We take the linear threshold model as the influence model. We show first the expressiveness of influence games showing that they capture the class of simple games. Then we characterize the computational complexity of various problems on influence games, including measures (length and width), values (Shapley-Shubik and Banzhaf) and properties (of teams and players). Finally, we analyze those problems for some particular extremal cases, with respect to the propagation of influence, showing tighter complexity characterizations.Peer ReviewedPostprint (author’s final draft

    Algorithmic and complexity aspects of simple coalitional games

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    Simple coalitional games are a fundamental class of cooperative games and voting games which are used to model coalition formation, resource allocation and decision making in computer science, artificial intelligence and multiagent systems. Although simple coalitional games are well studied in the domain of game theory and social choice, their algorithmic and computational complexity aspects have received less attention till recently. The computational aspects of simple coalitional games are of increased importance as these games are used by computer scientists to model distributed settings. This thesis fits in the wider setting of the interplay between economics and computer science which has led to the development of algorithmic game theory and computational social choice. A unified view of the computational aspects of simple coalitional games is presented here for the first time. Certain complexity results also apply to other coalitional games such as skill games and matching games. The following issues are given special consideration: influence of players, limit and complexity of manipulations in the coalitional games and complexity of resource allocation on networks. The complexity of comparison of influence between players in simple games is characterized. The simple games considered are represented by winning coalitions, minimal winning coalitions, weighted voting games or multiple weighted voting games. A comprehensive classification of weighted voting games which can be solved in polynomial time is presented. An efficient algorithm which uses generating functions and interpolation to compute an integer weight vector for target power indices is proposed. Voting theory, especially the Penrose Square Root Law, is used to investigate the fairness of a real life voting model. Computational complexity of manipulation in social choice protocols can determine whether manipulation is computationally feasible or not. The computational complexity and bounds of manipulation are considered from various angles including control, false-name manipulation and bribery. Moreover, the computational complexity of computing various cooperative game solutions of simple games in dierent representations is studied. Certain structural results regarding least core payos extend to the general monotone cooperative game. The thesis also studies a coalitional game called the spanning connectivity game. It is proved that whereas computing the Banzhaf values and Shapley-Shubik indices of such games is #P-complete, there is a polynomial time combinatorial algorithm to compute the nucleolus. The results have interesting significance for optimal strategies for the wiretapping game which is a noncooperative game defined on a network
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