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The small-world concept and its relationship with causalityCausality, presented in the previous chapter, require constant coarsening and simplification of the microscopic properties of the interacting system’s elements. Such extreme simplification is very useful for reducing the complexity of the element (and its corresponding states) into simple and quantifiable observablesObservable in establishing mathematical and computational methods to describe the essential phenomenology of the collective behavior of interconnected systems. This chapter provides a brief overview of which deductive and inductive mathematical modeling and causal inference play a role in systems theory and how the interconnectedness of systems determines the causal properties of complex systems. In this context, statistical physics and graph theory (complex networks) are relevant. Specifically, this chapter provides an overview of mathematical models for evaluating the observability of systems and their causal structure.

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A Brief Overview of Dynamic Complex Systems and Causal Inference

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  • 发表日期：

    2025年

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  • Juan Guillermo Diaz Ochoa

摘要

The small-world concept and its relationship with causalityCausality, presented in the previous chapter, require constant coarsening and simplification of the microscopic properties of the interacting system’s elements. Such extreme simplification is very useful for reducing the complexity of the element (and its corresponding states) into simple and quantifiable observablesObservable in establishing mathematical and computational methods to describe the essential phenomenology of the collective behavior of interconnected systems. This chapter provides a brief overview of which deductive and inductive mathematical modeling and causal inference play a role in systems theory and how the interconnectedness of systems determines the causal properties of complex systems. In this context, statistical physics and graph theory (complex networks) are relevant. Specifically, this chapter provides an overview of mathematical models for evaluating the observability of systems and their causal structure.