Blender to physical extensions

The inclusion of a functioning circuit in an animation requires a new associated file type. ".bncf" is a blender neural configuration file that establishes the physical relationship of the central control structure to the model. The proportionate control is done by methods that act in specific directions which conform to a single muscle group. Instead of defining the rotation, translation and deformation in a completely free manner, each action that proceeds must have an underlying muscle and a connection to a central control unit.

This models the system in the same way that matches the biological phenotype expression and allows changes to be made at the gene expression level to generate changes in the model and the actions of the model. Ultimately the bncf file describes the connectivity required to acheive the underlying motions. By combining all these things, it is possible to compile from a DNA sequence to the actions and establish a continuously higher neural like complexity that binds to the sub surface animation much like using common functions in a library file for an application.

At this level it is assumed that "model x" is known and information can be applied to the control interface in a layered addition for a specific composite set. Each of the parts must be present, like a graphics program must use GL, glut, stdio, or any other library that provides the lower level of functionality to execute a complex act.

It is not necessary to have all of the modules loaded in a common file when they are referenced as libraries of functions which are designed to operate in parallel coherently, without deadlock or interference.

The DNA for the higher functions is the next step of conversion or compile. When the model is complete it will allow me to interpolate from the DNA level, which changes can be beneficial and a general idea of the actions that might be taken by such an organism, before it is physically instantiated. Successive approximation of the steps of translation by measuring the relationship of the completed product to the expectations will allow a continuously more precise understanding of the underlying mechanism.