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A Simple Hierarchical Causality Primer

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  • Tim Gebbie

Abstract

We provide a brief primer for the idea behind formalising hierarchical causality in the context of complex systems. Here actors are not simply agents. Actors instantiate causation classes. Agents implement local dynamics in given levels or organisation in a given system. Hierarchical causality then describes how actor-level roles constrain, select, and organise agent-level behaviour across levels. The system then necessarily requires three additional structures. First, causation classes to abstract a given form of causal influence that an actor instantiates. Second, aggregation operators to move across the levels. Third, discrete event-time maps are required because the system comprises events, and the relation between local event counts and any global clock must be specified. Our formulation here is purposefully simple and discrete.

Suggested Citation

  • Tim Gebbie, 2026. "A Simple Hierarchical Causality Primer," Papers 2606.01979, arXiv.org, revised Jun 2026.
    • Handle: RePEc:arx:papers:2606.01979
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    References listed on IDEAS

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    1. Volker Grimm & Steven F. Railsback & Christian E. Vincenot & Uta Berger & Cara Gallagher & Donald L. DeAngelis & Bruce Edmonds & Jiaqi Ge & Jarl Giske & Jürgen Groeneveld & Alice S.A. Johnston & Alex, 2020. "The ODD Protocol for Describing Agent-Based and Other Simulation Models: A Second Update to Improve Clarity, Replication, and Structural Realism," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(2), pages 1-7.
    2. Matthew Dicks & Andrew Paskaramoorthy & Tim Gebbie, 2023. "Many learning agents interacting with an agent-based market model," Papers 2303.07393, arXiv.org, revised Aug 2024.
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