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    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/3911

    Título
    Mesoscopic effects in an agent-based bargaining model in regular lattices
    Autor
    Poza, David J.
    Santos Martín, José IgnacioAutoridad UBU Orcid
    Galán Ordax, José ManuelAutoridad UBU Orcid
    López Paredes, Adolfo
    Publicado en
    PLOS ONE. 2011, V. 6, n. 3, e17661
    Editorial
    Public Library of Science
    Fecha de publicación
    2011-03
    ISSN
    1932-6203
    DOI
    10.1371/journal.pone.0017661
    Résumé
    The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent’s most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.
    Materia
    Industrial management
    Gestión de empresas
    URI
    http://hdl.handle.net/10259/3911
    Versión del editor
    info:eu-repo/grantAgreement/JCyL/GREX251-2009
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    Poza-PlosOne_2011.pdf
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