The Architecture of Complexity [Part 1]
According to Herbert Simon, hierarchy is “one of the central structural schemes that the architect of complexity uses.” In his definition, a hierarchy “is composed of interrelated subsystems, each of the latter being in turn hierarchic in structure until we reach some lowest level of elementary subsystem.”
He goes on to explain why this hierarchy is important, starting with a story. In Simon’s analogy to two watchmakers, Hora and Tempus both manufacture high quality watches of the same complexity, but Hora “had designed them so that he could put together subassemblies of about ten elements each.” Tempus had no such subassemblies. Whenever Hora had to pause, he could pick up from where he left off, losing only a small part of his work. Tempus, should he pause, would lose all his work. Without stable subassemblies built in, Tempus would have to start again from zero.
Biology. “The lesson for biological evolution is quite clear and direct. The time required for the evolution of a complex form from simple elements depends critically on the numbers and distribution of potential intermediate stable forms.”
Empire building. Simon points out that historic empires (“successful” by definition) were composed of major subsystems; “if one would be Alexander, one should be born into a world where large stable political systems already exist.”
Problem Solving. “In problem solving, a partial result that represents recognizable progress toward the goal plays the role of stable assembly.” This is useful because “indications of progress spur further search in the same direction; lack of progress signals the abandonment of a line of search.”
Problem solving, then, “requires selective trial and error.” According to Simon, problem solving is “nothing more than varying mixtures of trial and error and selectivity,” using rules of thumb to assess which pathways to try. This selectivity is actually “feedback of information from the environment” typically of two forms:  Learned testing, or  Previous experience. “By simply trying again the paths that led to the earlier solution, or their analogues, trial-and-error search is greatly reduced or altogether eliminated.”
This reminds me of Cosma and his reference to Kevin Kelly’s Occam’s Razor interpretation.
As someone who loves to boil the ocean, this simple strategy seems immensely relieving. And yet, I wonder — does it become *too* easy to follow the most familiar path? The key, it seems, is to remember to listen to the feedback.
“The Architecture of Complexity,” from The Sciences of the Artificial
Author: Herbert Simon
I shall not undertake a formal definition of “complex systems.” Roughly, by a complex system I mean one made up of a large number of parts that have many interactions. […] In such systems, the whole is more than the sum of the parts.
Most physical and biological hierarchies are described in spatial terms. […] On the other hand, we propose to identify social hierarchies not by observing who lives close to whom but by observing who interacts with whom. These two points of view can be reconciled by defining hierarchy in terms of intensity of interaction.