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    Made withinDC&Austin
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    Home/Original/inverse
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    Inverse View

    It is not the case that Agent-based modeling is a more appropriate method for representing how scientists decide which research problems and strategies to pursue.

    ?Set your confidence on the premises below to see your aggregate.

    Reasons For

    2 perspectives
    Reason for 1 of 2
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    • 1.ABMs require prior theoretical commitments about which agent behaviors and decision rules are scientifically relevant, making them no less idealized than analytical models.
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    • 2.Weisberg and Muldoon's epistemic landscape ABMs have been shown to produce divergent results under minor parameter changes, undermining their claim to greater representational fidelity.
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    • 3.Representational heterogeneity in a model does not entail that the model accurately captures the causal mechanisms driving actual scientific decision-making.
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    Reason for 2 of 2
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    • 1.Kitcher's formal framework in 'The Advancement of Science' is explicitly normative, not descriptive, so empirical inadequacy about agent cognition is not a defeating objection.
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    • 2.Conflating the normative question of how scientists ought to allocate effort with the descriptive question of how they do decide undermines the original justificatory purpose of these models.
      ?

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    Reasons Against

    1 perspective
    Reason against
    ?
    • 1.Kitcher's and Strevens's models require idealized agents with full or uniform knowledge.
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    • 2.Actual scientists have imperfect, non-overlapping, and partial knowledge.
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    • 3.Agent-based modeling can represent heterogeneous, partial, and imperfect knowledge among agents.
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