Anomalous Systems Analysis for Archaeological Discovery Planning

Archaeological discovery planning increasingly relies on predictive models to allocate limited survey resources. While existing approaches—such as GIS-based suitability modeling, machine learning classifiers, and remote sensing—have demonstrated measurable success, they also exhibit persistent weaknesses: correlated evidence inflation, sampling bias, poor calibration, and inconsistent operational outcomes across regions and teams. This white paper presents a public, non-operational formulation of Anomalous Systems Analysis (ASA) adapted for archaeological discovery planning. ASA reframes prediction as decision optimization under uncertainty, rather than site revelation, and embeds ethical governance directly into the system architecture.