The regulation logic that controls process can lead to, built in, dynamic optimization.
For living organisms, creating new biological material that better suits the environmental demands is part of adapting through growth. This does not have to be goal directed but simply has to iteratively improve performance. This form of adaptation is part of overall growth.
For mechanical processes (that can't reproduce their own machinery) the restructuring of the processes may be a cost that reduces the overall growth rate of that business or process.
General control logic:
for two parallel processes that must both contribute equally to the product
if rate A > rate B then invest more (of growth or the product) back into B in the next time step
and vice verse
Systems Model:
Outcome from dynamic optimization can be:
smooth response where the machinery for in process 1 and 2 increase steadily
"sawtooth" - because of time step and lag, process 1 increases then it becomes in excess and then process 2 increases to catch up
"tail chasing" - the process is always lagging behind the environmental drivers and, in the worst scenario, always adapted for "yesterday's" conditions
Multi-scale regulation:
overlap of regulation times scale helps to avoid this "tail chasing" - see Chapter 4
thermostat metaphor for human response to heat is too simplistic
5 mechanisms with overlapping time scales
skin flushes
systemic increase in blood flow
sweating
ventilation (breating rate)
behavior (such as moving someplace cooler or fanning)
