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.
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页码：1237 / 1274
页数：38
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