Constrained coalition formation

Talal Rahwan, Tomasz Michalak, Edith Elkind, Piotr Faliszewski, Jacek Sroka, Michael Wooldridge, Nicholas R. Jennings

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

    Abstract

    The conventional model of coalition formation considers every possible subset of agents as a potential coalition. However, in many real-world applications, there are inherent constraints on feasible coalitions: for instance, certain agents may be prohibited from being in the same coalition, or the coalition structure may be required to consist of coalitions of the same size. In this paper, we present the first systematic study of constrained coalition formation (CCF). We propose a general framework for this problem, and identify an important class of CCF settings, where the constraints specify which groups of agents should/should not work together. We describe a procedure that transforms such constraints into a structured input that allows coalition formation algorithms to identify, without any redundant computations, all the feasible coalitions. We then use this procedure to develop an algorithm for generating an optimal (welfare-maximizing) constrained coalition structure, and show that it outperforms existing state-of-the-art approaches by several orders of magnitude.

    Original languageEnglish (US)
    Title of host publicationAAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference
    Pages719-725
    Number of pages7
    Volume1
    StatePublished - Nov 2 2011
    Event25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11 - San Francisco, CA, United States
    Duration: Aug 7 2011Aug 11 2011

    Other

    Other25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
    CountryUnited States
    CitySan Francisco, CA
    Period8/7/118/11/11

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

    Cite this

    Rahwan, T., Michalak, T., Elkind, E., Faliszewski, P., Sroka, J., Wooldridge, M., & Jennings, N. R. (2011). Constrained coalition formation. In AAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference (Vol. 1, pp. 719-725)

    Constrained coalition formation. / Rahwan, Talal; Michalak, Tomasz; Elkind, Edith; Faliszewski, Piotr; Sroka, Jacek; Wooldridge, Michael; Jennings, Nicholas R.

    AAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference. Vol. 1 2011. p. 719-725.

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

    Rahwan, T, Michalak, T, Elkind, E, Faliszewski, P, Sroka, J, Wooldridge, M & Jennings, NR 2011, Constrained coalition formation. in AAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference. vol. 1, pp. 719-725, 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11, San Francisco, CA, United States, 8/7/11.
    Rahwan T, Michalak T, Elkind E, Faliszewski P, Sroka J, Wooldridge M et al. Constrained coalition formation. In AAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference. Vol. 1. 2011. p. 719-725
    Rahwan, Talal ; Michalak, Tomasz ; Elkind, Edith ; Faliszewski, Piotr ; Sroka, Jacek ; Wooldridge, Michael ; Jennings, Nicholas R. / Constrained coalition formation. AAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference. Vol. 1 2011. pp. 719-725
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