28 research outputs found
Semivalues: weighting coefficients and allocations on unanimity games
This is a post-peer-review, pre-copyedit version of an article published in Optimization letters. The final authenticated version is available online at: http://dx.doi.org/10.1007/s11590-017-1224-8.Each semivalue, as a solution concept defined on cooperative games with a finite set of players, is univocally determined by weighting coefficients that apply to players’ marginal contributions. Taking into account that a semivalue induces semivalues on lower cardinalities, we prove that its weighting coefficients can be reconstructed from the last weighting coefficients of its induced semivalues. Moreover, we provide the conditions of a sequence of numbers in order to be the family of the last coefficients of any induced semivalues. As a consequence of this fact, we give two characterizations of each semivalue defined on cooperative games with a finite set of players: one, among all semivalues; another, among all solution concepts on cooperative games.Peer ReviewedPostprint (author's final draft
Ready for the design of voting rules?
The design of fair voting rules has been addressed quite often in the
literature. Still, the so-called inverse problem is not entirely resolved. We
summarize some achievements in this direction and formulate explicit open
questions and conjectures.Comment: 10 page
Probabilistic power indices for games with abstention
S'introdueixen vuit Ãndexs de poder que admeten una interpretació probabilÃstica per les normes de votació amb abstenció o amb tres nivells d'aprovació en l'entrada. S'analitzen les semblances i diferències entre els Ãndexs està ndards coneguts pels jocs simples i per les extensions per aquest context més general. Es conclou la feina proporcionant procediments basats en la generació de funcions per jocs(3,2) extensibles a jocs (j,k).Preprin
Political Influence in Multi-Choice Institutions: Cyclicity, Anonymity and Transitivity
We study political influence in institutions where members choose from among several options their levels of support to a collective goal, these individual choices determining the degree to which the goal is reached. Influence is assessed by newly defined binary relations, each of which compares any two individuals on the basis of their relative performance at a corresponding level of participation. For institutions with three levels of support (e.g., voting games in which each voter may vote "yes", "abstain", or vote "no"), we obtain three influence relations, and show that the strict component of each of them may be cyclical. The cyclicity of these relations contrasts with the transitivity of the unique influence relation of binary voting games. Weak conditions of anonymity are sufficient for each of them to be transitive. We also obtain a necessary and sufficient condition for each of them to be complete. Further, we characterize institutions for which the rankings induced by these relations, and the Banzhaf-Coleman and Shapley-Shubik power indices coincide. We argue that the extension of these relations to firms would be useful in efficiently allocating workers to different units of production. Applications to various forms of political and economic organizations are provided.Level-based influence relations, Multi-choice institutions, cyclicity, anonymity, transitivity
Bayesian Regression Markets
Machine learning tasks are vulnerable to the quality of data used as input.
Yet, it is often challenging for firms to obtain adequate datasets, with them
being naturally distributed amongst owners, that in practice, may be
competitors in a downstream market and reluctant to share information. Focusing
on supervised learning for regression tasks, we develop a \textit{regression
market} to provide a monetary incentive for data sharing. Our proposed
mechanism adopts a Bayesian framework, allowing us to consider a more general
class of regression tasks. We present a thorough exploration of the market
properties, and show that similar proposals in current literature expose the
market agents to sizeable financial risks, which can be mitigated in our
probabilistic setting.Comment: 46 pages, 11 figures, 2 table