We study the complexity of computing the Shapley value in games with externalities. We focus on two representations based on marginal contribution nets (embedded MC-nets and weighted MC-nets). Our results show that while weighted MC-nets are more concise than embedded MC-nets, they have slightly worse computational properties when it comes to computing the Shapley value.
翻译:我们研究了在带有外差因素的游戏中计算变形值的复杂性。 我们侧重于基于边际贡献网(嵌入的MC-nets和加权的MC-nets ) 的两个表述。 我们的结果表明,尽管加权的MC-nets比嵌入的MC-nets更简洁,但在计算变形值时它们的计算属性却稍差。