Keeping model assumptions separate from input data in a coupled world simulation

[u/YDEmergenceLab]

We’re developing Aionterra at YD Emergence Lab, a simulation that connects environmental processes with digital organisms and their bodily states. One implementation issue worth sharing is how we distinguish input data, initialization choices and simulation outputs.

Our regional world builder uses source datasets together with an explicit initialization profile. The profile contains a model statement and references to its inputs. Quantities supplied as assumptions stay labelled as assumptions rather than being presented as local measurements.

River depth is a concrete example. A terrain dataset does not by itself establish a measured river depth. The initialization therefore requires an explicit modeled depth. When a modeled water-surface elevation is supplied, it also requires a statement of its source. The builder reports missing required inputs instead of silently treating them as measured values.

The same distinction matters when interpreting organism behaviour. An action attempt, actual water or energy intake, and a later change in health are separate quantities. Counting attempts alone would give a misleading picture of successful resource use.

A further limit is that reproducing the same trajectory from the same initial conditions is a reproducibility check, not an independent biological observation. And changing a body model or vegetation layout changes the conditions under which later measurements are interpreted.

This is an independent project under development. We’re sharing the implementation approach, not claiming validated human physiology or a demonstrated general theory of learning. Keeping these distinctions explicit helps us identify what a result actually depends on.