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A Generic Approach To Coalition Formation

Author

Listed:
  • KRZYSZTOF R. APT

    (CWI, Science Park 123, 1098 XG Amsterdam, The Netherlands)

  • ANDREAS WITZEL

    (ILLC, University of Amsterdam, Plantage Muidergracht 24, 1018 TV Amsterdam, The Netherlands)

Abstract

We propose an abstract approach to coalition formation that focuses on simple merge and split rules transforming partitions of a group of players. We identify conditions under which every iteration of these rules yields a unique partition. The main conceptual tool is a specific notion of a stable partition. The results are parametrized by a preference relation between partitions of a group of players and naturally apply to coalitional TU-games, hedonic games and exchange economy games.

Suggested Citation

  • Krzysztof R. Apt & Andreas Witzel, 2009. "A Generic Approach To Coalition Formation," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 347-367.
    • Handle: RePEc:wsi:igtrxx:v:11:y:2009:i:03:n:s0219198909002352
    DOI: 10.1142/S0219198909002352
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    References listed on IDEAS

    as
    1. Marco A. Marini, 2007. "An Overview of Coalitions and Networks Formation Models for Economic Applications," Working Papers 0707, CREI Università degli Studi Roma Tre, revised 2007.
    2. Marco Marini, 2007. "An Overview of Coalition & Network Formation Models for Economic Applications," Working Papers 0712, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2007.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Vittorio Bilò & Angelo Fanelli & Michele Flammini & Gianpiero Monaco & Luca Moscardelli, 2018. "Nash Stable Outcomes in Fractional Hedonic Games: Existence, Efficiency and Computation," Post-Print hal-02089363, HAL.
    2. Andrew J. Collins & Sheida Etemadidavan & Wael Khallouli, 2020. "Generating Empirical Core Size Distributions of Hedonic Games using a Monte Carlo Method," Papers 2007.12127, arXiv.org.
    3. Tushar, Wayes & Saha, Tapan Kumar & Yuen, Chau & Azim, M. Imran & Morstyn, Thomas & Poor, H. Vincent & Niyato, Dustin & Bean, Richard, 2020. "A coalition formation game framework for peer-to-peer energy trading," Applied Energy, Elsevier, vol. 261(C).
    4. Mei, Jie & Chen, Chen & Wang, Jianhui & Kirtley, James L., 2019. "Coalitional game theory based local power exchange algorithm for networked microgrids," Applied Energy, Elsevier, vol. 239(C), pages 133-141.
    5. Changhua Yao & Lei Zhu & Yongxing Jia & Lei Wang, 2019. "Demand-aware traffic cooperation for self-organizing cognitive small-cell networks," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
    6. Areej A. Malibari & Daniyal Alghazzawi & Maha M. A. Lashin, 2021. "Coalition Formation among the Cooperative Agents for Efficient Energy Consumption," Sustainability, MDPI, vol. 13(15), pages 1-18, August.

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    More about this item

    Keywords

    Coalition formation; stable partition; merges and splits;
    All these keywords.

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C0 - Mathematical and Quantitative Methods - - General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

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