Universal Science of Complexity: Consistent Understanding of Ecological, Living and Intelligent System Dynamics

Physics – General Physics

Scientific paper

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13 pages, 28 eqs, 15 refs; Invited talk at the International Conference "Describing Complex Systems 2006" (Brijuni Islands, 12

Scientific paper

A major challenge of interdisciplinary description of complex system behaviour is whether real systems of higher complexity levels can be understood with at least the same degree of objective, "scientific" rigour and universality as "simple" systems of classical, Newtonian science paradigm. The problem is reduced to that of arbitrary, many-body interaction (unsolved in standard theory). Here we review its causally complete solution, the ensuing concept of complexity and applications. The discovered key properties of dynamic multivaluedness and entanglement give rise to a qualitatively new kind of mathematical structure providing an exact version of real system behaviour. The extended mathematics of complexity contains a truly universal definition of dynamic complexity, randomness (chaoticity), classification of all possible dynamic regimes, and a unifying principle of any system dynamics and evolution, the universal symmetry of complexity. Every real system has a non-zero (and actually high) value of unreduced dynamic complexity determining, in particular, "mysterious" behaviour of quantum systems and relativistic effects. The observed differences between various systems are due to different regimes and levels of their unreduced dynamic complexity. We outline applications of universal concept of dynamic complexity emphasising the case of "truly complex" systems from higher complexity levels (ecological and living systems, brain operation, intelligence and consciousness, autonomic information and communication systems) and show that the urgently needed progress in social and intellectual structure of civilisation inevitably involves qualitative transition to unreduced complexity understanding (we call it "revolution of complexity").

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