Semi-Artificial Models of Populations: Connecting Demography with Agent-Based Modelling

Eric Silverman, Jakub Bijak, Jason Noble, Viet Cao, Jason Hilton

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


    In this paper we present an agent-based model of the dynamics
    of mortality, fertility, and partnership formation in a closed population.
    One of our goals is to bridge the methodological and conceptual gaps
    that remain between demography and agent-based social simulation approaches.
    Model construction incorporates elements of both perspectives,
    with demography contributing empirical data on population dynamics,
    subsequently embedded in an agent-based model situated on a 2D grid
    space. While taking inspiration from previous work applying agent-based
    simulation methodologies to demography, we extend this basic concept
    to a complete model of population change, which includes spatial elements
    as well as additional agent properties. Given the connection to
    empirical work based on demographic data for the United Kingdom, this
    model allows us to analyse population dynamics on several levels, from
    the individual, to the household, and to the whole simulated population.
    We propose that such an approach bolsters the strength of demographic
    analysis, adding additional explanatory power.
    Original languageEnglish
    Title of host publicationAdvances in Computational Social Science: The Fourth World Congress (Agent-Based Social Systems)
    PublisherSpringer Japan
    Number of pages12
    ISBN (Print)9784431548461
    Publication statusPublished - 18 Apr 2014

    Bibliographical note

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