2013/12/12 by Daniel Zwillinger, Zwillinger, Daniel
Computer Science · Mathematics · #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Probability (math.PR) #cs.GT #math.PR
paper · pdf · doi:10.48550/arxiv.1312.3394
arxiv created 2013/12/12 · arxiv updated 2013/12/13
Voting power determines the "power" of individuals who cast votes; their power is based on their ability to influence the winning-ness of a coalition. Usually each individual acts alone, casting either all or none of their votes and is equally likely to do either. This paper extends this standard "random voting" model to allow probabilistic voting, partial voting, and correlated team voting. We extend the standard Banzhaf metric to account for these cases; our generalization reduces to the standard metric under "random voting", This new paradigm allows us to answer questions such as "In the 2013 US Senate, how much more unified would the Republicans have to be in order to have the same power as the Democrats in attaining cloture?"