A description and sensitivity analysis of the ArchMatNet agent-based model

被引:1
|
作者
Bischoff, Robert J. [1 ]
Padilla-Iglesias, Cecilia [2 ]
机构
[1] Arizona State Univ, Sch Human Evolut & Social Change, Tempe, AZ 85281 USA
[2] Univ Zurich, Dept Evolutionary Anthropol, Zurich, Switzerland
关键词
Agent-based model; Network analysis; Sensitivity analysis; Cultural transmission; Material culture; Archaeological record; Social network proxy; Hunter-gatherer networks; SOCIAL NETWORKS; CULTURAL TRANSMISSION; MOBILITY; TIME;
D O I
10.7717/peerj-cs.1419
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Archaeologists cannot observe face-to-face interactions in the past, yet methods derived from the analyses of social networks are often used to make inferences about patterns of past social interactions using material cultural remains as a proxy. We created the ArchMatNet agent-based model to explore the relationship between networks built from archaeological material and the past social networks that generated them. It was designed as an abstract model representing a wide variety of social systems and their dynamics: from hunter-gatherer groups to small-scale horticulturalists. The model is highly flexible, allowing agents to engage in a variety of activities (e.g., group hunting, visiting, trading, cultural transmission, migration, seasonal aggregations, etc.), and includes several parameters that can be adjusted to represent the social, demographic and historical dynamics of interest. This article examines how sensitive the model is to changes in these various parameters, primarily by relying on the one-factor-at-a-time (OFAT) approach to sensitivity analysis. Our purpose is for this sensitivity analyses to serve as a guide for users of the model containing information on how the model works, the types of agents and variables included, how parameters interact with one another, the model outputs, and how to make informed choices on parameter values.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] Sensitivity Analysis of an Empirical Agent-Based Model of District Heating Network Adoption
    Polhill, Gary
    Salt, Doug
    Craig, Tony
    Wilson, Ruth
    Colley, Kathryn
    ADVANCES IN COMPUTATIONAL INTELLIGENCE (IWANN 2021), PT II, 2021, 12862 : 118 - 127
  • [2] Parameter estimation and sensitivity analysis in an agent-based model of Leishmania major infection
    Dancik, Garrett M.
    Jones, Douglas E.
    Dorman, Karin S.
    JOURNAL OF THEORETICAL BIOLOGY, 2010, 262 (03) : 398 - 412
  • [3] Sensitivity analysis of an agent-based simulation model using reconstructability analysis
    Nunes, Andey M.
    Zwick, Martin
    Wakeland, Wayne
    INTERNATIONAL JOURNAL OF GENERAL SYSTEMS, 2021, 50 (03) : 319 - 338
  • [4] Global sensitivity/uncertainty analysis for agent-based models
    Fonoberova, Maria
    Fonoberov, Vladimir A.
    Mezic, Igor
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2013, 118 : 8 - 17
  • [5] A Bayesian sensitivity analysis applied to an Agent-based model of bird population response to landscape change
    Parry, Hazel R.
    Topping, Christopher J.
    Kennedy, Marc C.
    Boatman, Nigel D.
    Murray, Alistair W. A.
    ENVIRONMENTAL MODELLING & SOFTWARE, 2013, 45 (45) : 104 - 115
  • [6] Initial Conditions Sensitivity Analysis of a Two-Species Butterfly-Effect Agent-Based Model
    Berceanu, Cristian
    Patrascu, Monica
    MULTI-AGENT SYSTEMS, EUMAS 2022, 2022, 13442 : 60 - 78
  • [7] Sensitivity analysis of agent-based models: a new protocol
    Borgonovo, Emanuele
    Pangallo, Marco
    Rivkin, Jan
    Rizzo, Leonardo
    Siggelkow, Nicolaj
    COMPUTATIONAL AND MATHEMATICAL ORGANIZATION THEORY, 2022, 28 (01) : 52 - 94
  • [8] Sensitivity analysis of agent-based models: a new protocol
    Emanuele Borgonovo
    Marco Pangallo
    Jan Rivkin
    Leonardo Rizzo
    Nicolaj Siggelkow
    Computational and Mathematical Organization Theory, 2022, 28 : 52 - 94
  • [9] Which Sensitivity Analysis Method Should I Use for My Agent-Based Model?
    ten Broeke, Guus
    van Voorn, George
    Ligtenberg, Arend
    JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION, 2016, 19 (01):