Complexity of Computing the Shapley Value in Partition Function Form Games

被引：0

作者：

Skibski, Oskar ^{[1
]}

机构：

[1] Univ Warsaw, Inst Informat, PL-02097 Warsaw, Poland

来源：

JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH | 2023年 / 77卷

关键词：

COALITION STRUCTURE GENERATION; POWER INDEXES; EXTERNALITIES; CONNECTIVITY; CORE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We study the complexity of computing the Shapley value in partition function form games. We focus on two representations based on marginal contribution nets (embedded MC-nets and weighted MC-nets) and five extensions of the Shapley value. 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: two out of five extensions can be computed in polynomial time for embedded MC-nets and only one for weighted MC-nets.

引用

页码：1237 / 1274

页数：38

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