Suchergebnisse

Investigations of cooperation often use totally different definitions, ranging from any mutual activities, via pursuing mutually stipulated goals, to altruistic services to others. To develop an overarching framework to order these definitions, the paper studies cooperation in the widest sense, understood as mutual activity towards mutually accepted goal values. It considers goal‐setting processes preceding cooperation, and the resulting different systems of goal values pursed and the related levels of utility achieved by cooperating parties. These different systems of goal‐values and achieved levels of utility provide a framework to distinguish eight forms of cooperation: They may express (i) sharing ideals, (ii) agreement of equals, or (iii) of unequals; (iv) the uniting of cooperating units; (v) the agreement of representatives; (vi) the restricted integration of newcomers; (vii) hierarchical top‐down subjection; or (viii) altruistic bottom‐up subordination. Finally, it is shown that market exchange neither applies nor leads to any of these forms of cooperation. © 2018 John Wiley & Sons, Ltd.

AbstractThe paper analyses how the control of material flows needed by living systems determines evolutionary patterns. A simplification of Miller's living systems theory, distinguishing only three functional units, (i) production systems, (ii) storage, and (iii) controller structures, is used to investigate the importance of these units on various evolutionary stages. In the internal evolution of biological systems, storage is crucial to control the availability of intermediate products of autocatalytic cycles. This is the base for continuous production and maintenance of controller structures (brains). In the external, technical evolution storage enables building external production systems and controller structures (like computers). In the dyadic coevolution of living systems, control of material flows and/or storage enable power positions in interaction patterns ranging from competition for scarce resources, via market relations, to egalitarian cooperation. Such power positions open access to different markets and exclusive evolutionary options. Economic theory widely ignores that. Copyright © 2015 John Wiley & Sons, Ltd.

AbstractThe paper investigates if a living system according to Miller's living systems theory is a viable system according to Beer's viable systems theory and vice versa. Miller's and Beer's theories are briefly reviewed and translated into one cybernetic approach. The comparison of their functional and structural commonalties and differences shows: Miller's theory allows simple structures, below the scope of Beer's approach, which are nevertheless viable, as examples from biology, anthropology and economy show. Beer's viable systems can be derived form Miller's living systems theory, i.e. Beer deals only with issues of viability that emerge with complex living systems. Short considerations of large social units suggest that their structures are not unequivocally determined and may be viable while deviating from Beer's approach, too. Yet such structures can be derived from Miller's theory. It is concluded that Miller's living systems theory covers viability more completely than Beer's viable systems theory. Copyright © 2009 John Wiley & Sons, Ltd.

AbstractFeedback systems have often been considered as relevant for an understanding of the brain. But obviously most biological systems have a much more complicated structure. Surprisingly the functional and structural necessities determining the route from simple feedback systems to complex goal‐orientated systems like the brain have never been investigated. Therefore this paper studies systematically the possibilities for adding functional elements like sensors, memory, effectors etc. to a feedback system. Then it investigates which combinations of functional elements are necessary to get to working goal‐orientated systems. Based on that necessities and options of data organization and the resulting cognitive possibilities are analysed. This abstract analysis delivers design rules for complex—technical and biological—goal‐orientated systems and basic epistemological facts how additional functional elements can add to their cognitive abilities. Finally, a 'design for a simple brain' illustrates the application of these design rules. Copyright © 2009 John Wiley & Sons, Ltd.