Axiomatic characterization of game-theoretic network centralities

Oskar Skibski, Tomasz P. Michalak, Talal Rahwan

    Research output: Contribution to conferencePaper

    Abstract

    One of the fundamental research challenges in network science is the centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this paper, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been proposed based on this approach, it is still unknown what distinguishes this family of indices from the more classical ones. In this paper, we answer this question by providing the first axiomatic characterization of game-theoretic centralities. Specifically, we show that every centrality can be obtained following the game-theoretic approach, and show that two natural classes of game-theoretic centrality can be characterized by two intuitive properties pertaining to Myerson's notion of Fairness.

    Original languageEnglish (US)
    Pages698-705
    Number of pages8
    StatePublished - Jan 1 2017
    Event31st AAAI Conference on Artificial Intelligence, AAAI 2017 - San Francisco, United States
    Duration: Feb 4 2017Feb 10 2017

    Other

    Other31st AAAI Conference on Artificial Intelligence, AAAI 2017
    CountryUnited States
    CitySan Francisco
    Period2/4/172/10/17

    ASJC Scopus subject areas

    • Artificial Intelligence

    Cite this

    Skibski, O., Michalak, T. P., & Rahwan, T. (2017). Axiomatic characterization of game-theoretic network centralities. 698-705. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.

    Axiomatic characterization of game-theoretic network centralities. / Skibski, Oskar; Michalak, Tomasz P.; Rahwan, Talal.

    2017. 698-705 Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.

    Research output: Contribution to conferencePaper

    Skibski, O, Michalak, TP & Rahwan, T 2017, 'Axiomatic characterization of game-theoretic network centralities' Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States, 2/4/17 - 2/10/17, pp. 698-705.
    Skibski O, Michalak TP, Rahwan T. Axiomatic characterization of game-theoretic network centralities. 2017. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.
    Skibski, Oskar ; Michalak, Tomasz P. ; Rahwan, Talal. / Axiomatic characterization of game-theoretic network centralities. Paper presented at 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States.8 p.
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