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Geometrical distribution of agents based on a generalised Potts model

Author

Listed:
  • Alejandro Rivero

    (Universidad de Zaragoza
    Kampal Data Solutions)

  • Alfonso Tarancón

    (Universidad de Zaragoza
    Universidad de Zaragoza, Campus San Francisco)

  • Carlos Tarancón

    (Kampal Data Solutions)

Abstract

In collective local interaction systems with agents assigned to different profiles (categories, traits), the distribution of such profiles in the neighbourhood of any agent affects the exchange of ideas, a basic element in Collective Intelligence experiments. It is important to control this distribution experimentally, asking for criteria that should range from maximum homogeneity to maximum difference. We suggest a method where we obtain these criteria by adding an extra interaction term to the Q-state Potts model, producing a rich vacuum structure. By controlling the two parameters of the model, we can obtain different patterns for the geometrical distribution of the agents. We study the transitions and phase diagram of this model, considering the physics at constant magnetization, and show that the states correspond to a large diversity of mixing patterns, directly applicable to agent distribution in CI experiments. Graphical abstract

Suggested Citation

  • Alejandro Rivero & Alfonso Tarancón & Carlos Tarancón, 2025. "Geometrical distribution of agents based on a generalised Potts model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 98(9), pages 1-8, September.
  • Handle: RePEc:spr:eurphb:v:98:y:2025:i:9:d:10.1140_epjb_s10051-025-01005-1
    DOI: 10.1140/epjb/s10051-025-01005-1
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    1. Hildegard Meyer-Ortmanns, 2003. "Immigration, Integration And Ghetto Formation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 311-320.
    2. L. Gauvin & J. Vannimenus & J.-P. Nadal, 2009. "Phase diagram of a Schelling segregation model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 70(2), pages 293-304, July.
    3. Alexander J. Stewart & Mohsen Mosleh & Marina Diakonova & Antonio A. Arechar & David G. Rand & Joshua B. Plotkin, 2019. "Information gerrymandering and undemocratic decisions," Nature, Nature, vol. 573(7772), pages 117-121, September.
    4. Christian Schulze, 2005. "Potts-Like Model For Ghetto Formation In Multi-Cultural Societies," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 351-355.
    5. D. Stauffer & H. Meyer-Ortmanns, 2004. "SIMULATION OF CONSENSUS MODEL OF DEFFUANTet al.ON A BARABÁSI–ALBERT NETWORK," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 241-246.
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