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Learning Context-Sensitive Norms under Uncertainty

Published:27 January 2019Publication History

ABSTRACT

Norms and conventions play a central role in maintaining social order in multi-agent societies [2, 5]. I study the problem of how these norms and conventions can be learned from observation of heterogeneous sources, under conditions of uncertainty. This is necessary as it is not enough to simply hard code a set of norms into a new agent prior to entering society because norms can evolve over time as agents enter and leave the society [9].

References

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      • Published in

        cover image ACM Conferences
        AIES '19: Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society
        January 2019
        577 pages
        ISBN:9781450363242
        DOI:10.1145/3306618

        Copyright © 2019 Owner/Author

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        • Published: 27 January 2019

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