Axiomatic characterization of game-theoretic centrality

Oskar Skibski, Tomasz P. Michalak, Talal Rahwan

Research output: Contribution to journalArticle

Abstract

One of the fundamental research challenges in network science is centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this article, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been recently proposed based on this approach, it is still unknown how general is the game-theoretic approach to centrality and what distinguishes some game-theoretic centralities from others. In this article, we attempt to answer this question by providing the first axiomatic characterization of game-theoretic centralities. Specifically, we show that every possible centrality measure can be obtained following the game-theoretic approach. Furthermore, we study three natural classes of game-theoretic centrality, and prove that they can be characterized by certain intuitive properties pertaining to the well-known notion of Fairness due to Myerson.

Original languageEnglish (US)
Pages (from-to)33-68
Number of pages36
JournalJournal of Artificial Intelligence Research
Volume62
DOIs
StatePublished - May 1 2018

ASJC Scopus subject areas

  • Artificial Intelligence

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