The three basic mechanisms of averaging, feedback and division of labor give us a first idea of a how a CMM [Collective Mental Map] can be developed … - Francis Heylighen
" "The three basic mechanisms of averaging, feedback and division of labor give us a first idea of a how a CMM [Collective Mental Map] can be developed in the most efficient way, that is, how a given number of individuals can achieve a maximum of collective problem-solving competence. A collective mental map is developed basically by superposing a number of individual mental maps. There must be sufficient diversity among these individual maps to cover an as large as possible domain, yet sufficient redundancy so that the overlap between maps is large enough to make the resulting graph fully connected, and so that each preference in the map is the superposition of a number of individual preferences that is large enough to cancel out individual fluctuations. The best way to quickly expand and improve the map and fill in gaps is to use a positive feedback that encourages individuals to use high preference paths discovered by others, yet is not so strong that it discourages the exploration of new paths.
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About Francis Heylighen
Francis Paul Heylighen (born 1960) is a Belgian cyberneticist, best known for his contributions to the evolutionary-cybernetic worldview developed in the Project, the modelling of the Internet as a , and the theories of and .
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Francis Paul Heylighen
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Additional quotes by 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
Many of the core ideas of cybernetics have been assimilated by other disciplines, where they continue to influence scientific developments. Other important cybernetic principles seem to have been forgotten, though, only to be periodically rediscovered or reinvented in different domains. Some examples are the rebirth of neural networks, first invented by cyberneticists in the 1940's, in the late 1960's and again in the late 1980's; the rediscovery of the importance of autonomous interaction by robotics and AI in the 1990's; and the significance of positive feedback effects in complex systems, rediscovered by economists in the 1990's. Perhaps the most significant recent development is the growth of the complex adaptive systems movement, which, in the work of authors such as John Holland, Stuart Kauffman and Brian Arthur and the subfield of , has used the power of modern computers to simulate and thus experiment with and develop many of the ideas of cybernetics. It thus seems to have taken over the cybernetics banner in its mathematical modelling of complex systems across disciplinary boundaries, however, while largely ignoring the issues of goal-directedness and control.
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