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Interleaving multi-agent systems and social networks for organized adaptation

Author

Listed:
  • Jeremy Pitt

    (Imperial College London)

  • Daniel Ramirez-Cano

    (Imperial College London)

  • Moez Draief

    (Imperial College London)

  • Alexander Artikis

    (National Centre for Scientific Research “Demokritos”)

Abstract

Ad hoc networks can be formed from arbitrary collections of sensors, mobile routers, or business processes. These networks are open systems, in the sense that the network nodes share a common language but do not necessarily share a common goal or common knowledge, and there is no centralised controller or global data repository. Such systems have numerous advantages in terms of enabling autonomous, heterogeneous components to achieve individual goals without central direction and with only partial knowledge. However, operational problems stem from potential conflicts over resource allocation, miscommunication, and sub-ideal operation, and the general need of embedded systems to change behaviour according to changes in the environment. To address these problems, we propose to converge aspects of norm-governed specification from distributed multi-agent systems, opinion formation from social networks, and voting procedures from computational social choice. In particular, we develop a prototype system which interleaves gossiping, expressed preferences (voting) and norms, to configure rules and assign roles. This is another demonstration of the use of socially-inspired mechanisms for regulation of decentralised systems and a key step towards the realization of organized adaptation for open multi-agent systems.

Suggested Citation

  • Jeremy Pitt & Daniel Ramirez-Cano & Moez Draief & Alexander Artikis, 2011. "Interleaving multi-agent systems and social networks for organized adaptation," Computational and Mathematical Organization Theory, Springer, vol. 17(4), pages 344-378, November.
  • Handle: RePEc:spr:comaot:v:17:y:2011:i:4:d:10.1007_s10588-011-9089-3
    DOI: 10.1007/s10588-011-9089-3
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    References listed on IDEAS

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    1. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    2. Draief, Moez, 2006. "Epidemic processes on complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(1), pages 120-131.
    3. Michael K. Buckland, 1991. "Information as thing," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(5), pages 351-360, June.
    4. Guillaume Deffuant & David Neau & Frederic Amblard & Gérard Weisbuch, 2000. "Mixing beliefs among interacting agents," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 87-98.
    5. Michael Buckland, 1991. "Rejoinder to “Information as thing”," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(10), pages 758-758, December.
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    Cited by:

    1. Jianjun Lu & Shozo Tokinaga, 2016. "Cluster fluctuation in two-dimensional lattices with local interactions," Computational and Mathematical Organization Theory, Springer, vol. 22(2), pages 237-259, June.
    2. Jianjun Lu & Shozo Tokinaga, 2013. "Analysis of cluster formations on planer cells based on genetic programming," Computational and Mathematical Organization Theory, Springer, vol. 19(4), pages 426-445, December.

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