By Vladimir S. Lerner
Information Macrodynamics (IMD) belong to an interdisciplinary technological know-how that represents a brand new theoretical and computer-based technique for a procedure informational descriptionand improvement,including quite a few actions in such components as pondering, clever approaches, communications, administration, and different nonphysical matters with their mutual interactions, informational superimposition, and theinformation transferredbetweeninteractions. The IMD is predicated at the implementation of a unmarried idea by means of a distinct mathematical precept and formalism, instead of on a synthetic mixture of many arbitrary, auxiliary ideas and/or postulates and diversified mathematical matters, corresponding to the sport, automata, disaster, logical operations theories, and so forth. this idea is explored mathematically utilizing classical arithmetic as calculus of version and the chance thought, that are effective sufficient, with no need to developnew,specifiedmathematical systemicmethods. The formal IMD version instantly comprises the comparable effects from different fields, corresponding to linear, nonlinear, collective and chaotic dynamics, balance idea, thought of knowledge, actual analogies of classical and quantum mechanics, irreversible thermodynamics, andkinetics. the most IMD target is to bare the data regularities, mathematically expressed via the thought of edition precept (VP), as a mathematical software to extractthe regularities and outline the version, whichdescribes theregularities. The IMD regularities and mechanisms are the result of the analytical strategies and aren't retained by way of logical argumentation, rational creation, and an inexpensive dialogue. The IMD's details machine modeling formalism contains a man or woman (as an observer, provider and manufacturer ofinformation), with a recovery of the version throughout the objectobservations.
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Extra resources for Variation Principle in Informational Macrodynamics
8] to exist. Computer simulation of the model's adaptive self-organizing process shows that at small n, a number of neighboring subsystems with a similar complexity does exist. With growing n, the number of close-complex neighboring subsystems decreases sharply. The MC defines the degree of the macrosystem organization and the resulting entropy increment that is able to overcome a crucial limit of complexity, creating self -organization. As the MC-complexity increased, the gap between the dynamic and geometrical properties of the nearest subsystems increased radically.
The IN models the transformation of initial linear chain into three dimensional triplet's organization, based on the variation minimax principle for information functional. 11. Macrosystemic Complexity Algorithmization of the information values of the network nodes determines the minimal IN's spectrum of the quantities of information. The restoration of the hierarchy of the identified nodes yields a quantitative measure of the level of systemic organization, evaluated by the function of informational macrosystemic dynamic complexity (MC).
A macrosystem, that possesses a negentropy maximum (at y = 0), is most "active" for self-organization. This model's y = 0 can only be approached, but not reached, because (as it was shown) the complexity of such a system becomes equal to 00. This means an impossibility of the complete elimination of the uncertainty of any macrosystem. Moreover, because each macrostate is wrapped in the uncertainly zone, none of the macrostates can be measured with zero error. The IN's code and its language contain the intrinsic uncertain errors as an ability to convey a bound information macrostructure, which imposes the limitations on the language correctness.
Variation Principle in Informational Macrodynamics by Vladimir S. Lerner