Shapley Values in Weighted Voting Games with Random Weights

We investigate the distribution of the well-studied Shapley–Shubik values in weighted voting games where the agents are stochastically determined. The Shapley-Shubik value measures the voting power of an agent, in typical collective decision making systems. While easy to estimate empirically given the parameters of a weighted voting game, the Shapley values are notoriously hard to reason about analytically. We propose a probabilistic approach in which the agent weights are drawn i.i.d. from some known exponentially decaying distribution. We provide a general closed-form characterization of the highest and lowest expected Shapley values in such a game, as a function of the parameters of the underlying distribution. To do so, we give a novel reinterpretation of the stochastic process that generates the Shapley variables as a renewal process. We demonstrate the use of our results on the uniform and exponential distributions. Furthermore, we show the strength of our theoretical predictions on several synthetic datasets.