arXiv: cs.AI preprintsInternational5 November 2026
From Type to Token: Petri Nets, Individual Token Philosophy, and Individualized Causal Effects
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arXiv:2611.05703v1 Announce Type: new Abstract: Structural Causal Models and Bayesian Networks are the dominant framework for representing causal relations. They are fundamentally type-level formalisms since their estimands, Average Treatment Effects and Conditional Average Treatment Effects, are properties of distributions over populations, not of individual units. When treatment effects exhibit unbounded heterogeneity, these estimands collapse. What persists is the structural, token-level core of causation. We argue that Petri Nets under the Individual Token Philosophy are the natural repres
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