Why Things Develop:
Development and dissolution are basic characteristics of a wide variety
of systems. Among the latter are biological ones, but also non-living systems
like, for example, geological ones, and of course also social systems. As has
been known for a long time, decay processes in the physical and biological
domains are determined by the entropy law. However, processes of the emergence
of new structures, or of organizational forms, have become a topic of broad
scientific investigation only during the last third of the twentieth century.
Based on the studies of the phenomenon of self-organization (or
emergence), new approaches have emerged in recent years to understand the abstract
machines behind structure generating and structure changing processes. This has
lead to the design of nonlinear models for general systems, which, among
others, are also applicable to historical processes. (See, for example, M. de
Landa, “A Thousand Years of Nonlinear History”.)
Some of the contemporary instruments for the simulation of
correspondingly complex systems on the computer are briefly reviewed, like,
e.g., genetic algorithms and cellular automata. It is shown that the emergence
of an “arrow of time” in biological, and even in social systems, can be
explained on a firm basis. In doing so, decisive roles are attributed to a) the
presence of recursive processes (like replications, for example) and b)
significant fluctuations around mean values. Such systems can often be
characterized by the self-organization of recursive “probes” in the space of
potential forms of their organization. In sufficiently complex systems, the
latter may emerge by their intrinsic dynamics (as in systems shown here to be
characterized by “hierarchically emergent fractal evolution”), i.e.,
independent of any external control mechanisms.