Procela: Epistemic Governance in Mechanistic Simulations Under Structural Uncertainty
Mechanistic simulations typically assume fixed ontologies: variables, causal relationships, and resolution policies are static. This assumption fails when the true causal structure is contested or unidentifiable-as in antimicrobial resistance (AMR) spread, where contact, environmental, and selection ontologies compete. We introduce Procela, a Python framework where variables act as epistemic authorities that maintain complete hypothesis memory, mechanisms encode competing ontologies as causal units, and governance observes epistemic signals and mutates system topology at runtime. This is the first framework where simulations test their own assumptions. We instantiate Procela for AMR in a ...
| Authors | Kinson Vernet |
|---|---|
| Primary category | physics.comp-ph |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
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