Paths to Interminacy

The re-awakening of interest in analog processes via robotics is fascinating to me for a particular reason. Computer programming is, I would say, notoriously or even fiendishly deterministic and inflexible. Yet (as the chaos theory video clip and the Brian Eno / Will Wright video demonstrate) programming can be used to produce indeterminacy/generativity if the programmer keeps the objects and interaction-rules simple and provides a way for the interactivity to build on itself (i.e., via simple iteration/repetition).

The robotics example is the same in principle. Each bug features a collection of simple intra-bug elements (in other words the actions it can perform --e.g., walking, perhaps simple-sensing, perhaps turning etc.). A bug's mobility provides the iteration: it just keeps trying to do whatever it is capable of doing.

Setting multiple bugs let loose in an environment ramps the complexity up (because the sum of types of interactions multiplies) but in a self-similar way the principle is the same: now what you have is a collection of simple bugs, each of which is simple unto itself, interacting simply with an environment that now includes each other (many more possible sensing opportunities, etc.).

In the computational venue or context, the critters and the environment (for example the game environment in the Wright/Eno video) are simply virtual. They are created with language/code processes, tools, and materials. The bugs are created with electronic processes, tools, and materials and move in the f2f environment.

In the biological setting, chemistry anyone? I am out of my league or knowledge-zone here, but talking about simple elements in combination and interaction producing complex results sounds a bit like the periodic table of the elements/atoms, molecules, and chemical reactions.

Can generativity be understood as learning in the key of life?