While a classic mathematical notation describes a scenario precisely and well defined in constants of its inner functions, NMPC-Graphs describe functions of a scenario only qualitatively. NMPC-Graphs are well suited to describe a hypothesis on human group behavior and econometric scenarios.

These qualitative functions allow to translate natural language into a NMPC-Graph and vice versa. The indefiniteness of natural language in some way also can be found within a NMPC-Graph. The NMPC-Graph was invented to allow for a hypothesis being expressed not to vaguely and not to precisely.

However, NMPC-Graphs are only indeterminate from a certain perspective. In fact, they are founded in a mathematical definition which allows for calculating precisely quantified functions from their qualitative relationships if there is enough historic data available. The calculation happens via an AI driven regression algorithm in a way that historic data can be reproduced best. This regression algorithm resides at the heart of CYNERELOâ„¢ software.

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