The practice of agent-based model visualization

Alan Dorin, Nicholas Geard

    Research output: Contribution to journalArticleResearchpeer-review

    Abstract

    We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual-and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

    Original languageEnglish
    Pages (from-to)271-289
    Number of pages19
    JournalArtificial Life
    Volume20
    Issue number2
    DOIs
    Publication statusPublished - 1 Jan 2014

    Keywords

    • Agent-based model
    • Individual-based model
    • Virtual ecosystem
    • Visualization

    Cite this

    Dorin, Alan ; Geard, Nicholas. / The practice of agent-based model visualization. In: Artificial Life. 2014 ; Vol. 20, No. 2. pp. 271-289.
    @article{7e0bb6d280cd4471a134b9f7dd0c533b,
    title = "The practice of agent-based model visualization",
    abstract = "We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual-and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.",
    keywords = "Agent-based model, Individual-based model, Virtual ecosystem, Visualization",
    author = "Alan Dorin and Nicholas Geard",
    year = "2014",
    month = "1",
    day = "1",
    doi = "10.1162/ARTL_a_00129",
    language = "English",
    volume = "20",
    pages = "271--289",
    journal = "Artificial Life",
    issn = "1064-5462",
    publisher = "Massachusetts Institute of Technology Press",
    number = "2",

    }

    The practice of agent-based model visualization. / Dorin, Alan; Geard, Nicholas.

    In: Artificial Life, Vol. 20, No. 2, 01.01.2014, p. 271-289.

    Research output: Contribution to journalArticleResearchpeer-review

    TY - JOUR

    T1 - The practice of agent-based model visualization

    AU - Dorin, Alan

    AU - Geard, Nicholas

    PY - 2014/1/1

    Y1 - 2014/1/1

    N2 - We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual-and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

    AB - We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual-and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

    KW - Agent-based model

    KW - Individual-based model

    KW - Virtual ecosystem

    KW - Visualization

    UR - http://www.scopus.com/inward/record.url?scp=84901620698&partnerID=8YFLogxK

    U2 - 10.1162/ARTL_a_00129

    DO - 10.1162/ARTL_a_00129

    M3 - Article

    VL - 20

    SP - 271

    EP - 289

    JO - Artificial Life

    JF - Artificial Life

    SN - 1064-5462

    IS - 2

    ER -