Artificial evolution for the detection of group identities in complex artificial societies

Corrado Grappiolo, Julian Togelius, Georgios N. Yannakakis

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper aims at detecting the presence of group structures in complex artificial societies by solely observing and analysing the interactions occurring among the artificial agents. Our approach combines: (1) an unsupervised method for clustering interactions into two possible classes, namely ingroup and out-group, (2) reinforcement learning for deriving the existing levels of collaboration within the society, and (3) an evolutionary algorithm for the detection of group structures and the assignment of group identities to the agents. Under a case study of static societies - i.e. the agents do not evolve their social preferences - where agents interact with each other by means of the Ultimatum Game, our approach proves to be successful for small-sized social networks independently on the underlying social structure of the society; promising results are also registered for mid-size societies.

    Original languageEnglish (US)
    Title of host publicationIEEE Symposium on Artificial Life (ALIFE)
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages126-133
    Number of pages8
    Volume2013-January
    EditionJanuary
    DOIs
    StatePublished - 2013
    Event4th IEEE International Symposium on Artificial Life, IEEE ALIFE 2013 - Singapore, Singapore
    Duration: Apr 16 2013Apr 19 2013

    Other

    Other4th IEEE International Symposium on Artificial Life, IEEE ALIFE 2013
    CountrySingapore
    CitySingapore
    Period4/16/134/19/13

    Fingerprint

    Group Structure
    Reinforcement learning
    Evolutionary algorithms
    Social Support
    Cluster Analysis
    Learning
    Reinforcement (Psychology)

    Keywords

    • Artificial societies
    • Emergence of complexity
    • Evolutionary computation
    • Group identity detection

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computational Theory and Mathematics
    • Computer Vision and Pattern Recognition
    • Biochemistry, Genetics and Molecular Biology(all)

    Cite this

    Grappiolo, C., Togelius, J., & Yannakakis, G. N. (2013). Artificial evolution for the detection of group identities in complex artificial societies. In IEEE Symposium on Artificial Life (ALIFE) (January ed., Vol. 2013-January, pp. 126-133). [6602441] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ALIFE.2013.6602441

    Artificial evolution for the detection of group identities in complex artificial societies. / Grappiolo, Corrado; Togelius, Julian; Yannakakis, Georgios N.

    IEEE Symposium on Artificial Life (ALIFE). Vol. 2013-January January. ed. Institute of Electrical and Electronics Engineers Inc., 2013. p. 126-133 6602441.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Grappiolo, C, Togelius, J & Yannakakis, GN 2013, Artificial evolution for the detection of group identities in complex artificial societies. in IEEE Symposium on Artificial Life (ALIFE). January edn, vol. 2013-January, 6602441, Institute of Electrical and Electronics Engineers Inc., pp. 126-133, 4th IEEE International Symposium on Artificial Life, IEEE ALIFE 2013, Singapore, Singapore, 4/16/13. https://doi.org/10.1109/ALIFE.2013.6602441
    Grappiolo C, Togelius J, Yannakakis GN. Artificial evolution for the detection of group identities in complex artificial societies. In IEEE Symposium on Artificial Life (ALIFE). January ed. Vol. 2013-January. Institute of Electrical and Electronics Engineers Inc. 2013. p. 126-133. 6602441 https://doi.org/10.1109/ALIFE.2013.6602441
    Grappiolo, Corrado ; Togelius, Julian ; Yannakakis, Georgios N. / Artificial evolution for the detection of group identities in complex artificial societies. IEEE Symposium on Artificial Life (ALIFE). Vol. 2013-January January. ed. Institute of Electrical and Electronics Engineers Inc., 2013. pp. 126-133
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