HERBERT SIMON, one of the founding fathers of systems theory and artificial intelligence, identified hierarchical recursion as a fundamental feature of computational systems. In a seminal 1962 paper “The Architecture of Complexity”, Simon claims that “It may not be entirely vain, however, to search for common properties among diverse kinds of complex systems”. This search for common properties (patterns, harmony, rhythms and more…) in complex systems (emotions, death, time, and more) which refers “to all complex systems analyzable into successive sets of subsystems” (Simon, 1962) has ramifications for many systems (from mathematics to physiology to ecosystems to culture).
Recursion(L-systems, fractals, and more..) in living structures, linguistics, and digital systems points to a deep continuity between life, language and computation.
ALBERT-LÁSZLÓ BARABÁSI, 45 years later published a paper with exactly the same title “The Architecture of Complexity” (August 2007, IEEE Control Systems Magazine). He too identifies the unifying force of network paradigms:
Networks exist everywhere and at every scale. The brain is a network of nerve cells connected by axons, while cells are networks of molecules connected by biochemical reactions. Societies, too, are networks of people linked by friendship, family, and professional ties. On a larger scale, food webs and ecosystems can be represented as networks of species. Furthermore, networks pervade technology; examples include the Internet, power grids, and transportation systems. Even the language used to convey thought is a network of words connected by syntactic relationships.
By identifying the structures and principles of networks, Barabási hopes to articulate a science of systems (he sees network theory as a prerequisite for a robust science of complex systems). Empirically-validated network properties such as scale-free (non-random power laws), small world (connecting each to the next “the typical number of clicks between two Web pages is around 19”), and preferential attachment (the probability of links influenced by previous links) have implications for the Internet and for epidemics.
The architecture of complexity continues to expand.