With the growing interest in complex adaptive systems, artificial life, swarms and simulated societies, the concept of “collective intelligence” is c… - Francis Heylighen

Science, and physics in particular, has developed out of the Newtonian paradigm of mechanics. In this world view, every phenomenon we observe can be reduced to a collection of atoms or particles, whose movement is governed by the deterministic laws of nature. Everything that exists now has already existed in some different arrangement in the past, and will continue to exist so in the future. In such a philosophy, there seems to be no place for novelty or creativity

Cybernetics as a specific field grew out of a series of interdisciplinary meetings held from 1944 to 1953 that brought together a number of noted post-war intellectuals, including Wiener, John von Neumann, Warren McCulloch, Claude Shannon, Heinz von Foerster, W. Ross Ashby, Gregory Bateson and Margaret Mead. Hosted by the Josiah Macy Jr. Foundation, these became known as the Macy Conferences on Cybernetics. From its original focus on machines and animals, cybernetics quickly broadened to encompass minds (e.g. in the work of Bateson and Ashby) and social systems (e.g. Stafford Beer's management cybernetics), thus recovering Plato's original focus on the control relations in society. Through the 1950s, cybernetic thinkers came to cohere with the school of General Systems Theory (GST), founded at about the same time by Ludwig von Bertalanffy, as an attempt to build a unified science by uncovering the common principles that govern open, evolving systems. GST studies systems at all levels of generality, whereas Cybernetics focuses more specifically on goal-directed, functional systems which have some form of control relation.

(Systems science) does not aim to find the one true representation for a given type of systems (e.g. physical, chemical or biological systems), but to formulate general principles about how different representations of different systems can be constructed so as to be effective in problem-solving.