CHRONO-ARCH: A Computational Framework for Temporal Archaeology and Civilizational Dynamics Using AI and Complex Systems Modeling

CHRONO-ARCH introduces a computational framework for modeling civilizations as nonlinear, temporally evolving dynamical systems embedded in environmental, economic, and networked interaction fields. Unlike traditional archaeological approaches that rely on static reconstruction, the framework formulates civilizations as coupled spatiotemporal systems governed by differential dynamics, probabilistic state transitions, and evolving interaction graphs. The core system is expressed as a nonlinear operator-valued ordinary differential equation over a time-dependent graph, augmented with a Fokker-Planck probabilistic layer and a causal inference module. All components are formally specified, computationally interpretable, and grounded in measurable variables. The framework enables simulation of long-term civilizational trajectories, inference of hidden historical structures, collapse modeling as phase transitions, and counterfactual historical analysis using formal causal reasoning.