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Information Macrodynamics (IMD) belong to an interdisciplinary
science that represents a new theoretical and computer-based
methodology for a system informational descriptionand improvement,
including various activities in such areas as thinking, intelligent
processes, communications, management, and other nonphysical
subjects with their mutual interactions, informational
superimposition, and theinformation transferredbetweeninteractions.
The IMD is based on the implementation of a single concept by a
unique mathematical principle and formalism, rather than on an
artificial combination of many arbitrary, auxiliary concepts and/or
postulates and different mathematical subjects, such as the game,
automata, catastrophe, logical operations theories, etc. This
concept is explored mathematically using classical mathematics as
calculus of variation and the probability theory, which are potent
enough, without needing to developnew, specifiedmathematical
systemicmethods. The formal IMD model automatically includes the
related results from other fields, such as linear, nonlinear,
collective and chaotic dynamics, stability theory, theory of
information, physical analogies of classical and quantum mechanics,
irreversible thermodynamics, andkinetics. The main IMD goal is to
reveal the information regularities, mathematically expressed by
the considered variation principle (VP), as a mathematical tool to
extractthe regularities and define the model, whichdescribes
theregularities. The IMD regularities and mechanisms are the
results of the analytical solutions and are not retained by logical
argumentation, rational introduction, and a reasonable discussion.
The IMD's information computer modeling formalism includes a human
being (as an observer, carrier and producer ofinformation), with a
restoration of the model during the objectobservations.
Informational Macrodynamics (IMD) presents the unified information
systemic approach with common information language for modeling,
analysis and optimization of a variety of interactive processes,
such as physical, biological, economical, social, and
informational, including human activities. Comparing it with
thermodynamics, which deals with transformation energy and
represents a theoretical foundation of physical technology, IMD
deals with transformation information, and can be considered a
theoretical foundation of Information Computer Technology (ICT).
ICT includes but is not limited to applied computer science,
computer information systems, computer and data communications,
software engineering, and artificial intelligence. In ICT,
information flows from different data sources, and interacts to
create new information products. The information flows may interact
physically or via their virtual connections, initiating an
information dynamic process that can be distributed in space. As in
physics, a problem is understanding general regularities of the
information processes in terms of information law, for the
engineering and technological design, control, optimization, and
development of computer technology, operations, manipulations, and
management of real information objects. Information Systems
Analysis and Modeling: An Informational Macrodynamics Approach
belongs to an interdisciplinary science that represents the new
theoretical and computer-based methodology for system informational
description and improvement, including various activities in such
interdisciplinary areas as thinking, intelligent processes,
management, and other nonphysical subjects with their mutual
interactions, informational superimpositions, and the information
transferred between interactions. Information Systems Analysis and
Modeling: An Informational Macrodynamics Approach can be used as a
textbook or secondary text in courses on computer science,
engineering, business, management, education, and psychology and as
a reference for research and industry.
Information Macrodynamics (IMD) belong to an interdisciplinary
science that represents a new theoretical and computer-based
methodology for a system informational descriptionand
improvement,including various activities in such areas as thinking,
intelligent processes, communications, management, and other
nonphysical subjects with their mutual interactions, informational
superimposition, and theinformation transferredbetweeninteractions.
The IMD is based on the implementation of a single concept by a
unique mathematical principle and formalism, rather than on an
artificial combination of many arbitrary, auxiliary concepts and/or
postulates and different mathematical subjects, such as the game,
automata, catastrophe, logical operations theories, etc. This
concept is explored mathematically using classical mathematics as
calculus of variation and the probability theory, which are potent
enough, without needing to developnew,specifiedmathematical
systemicmethods. The formal IMD model automatically includes the
related results from other fields, such as linear, nonlinear,
collective and chaotic dynamics, stability theory, theory of
information, physical analogies of classical and quantum mechanics,
irreversible thermodynamics, andkinetics. The main IMD goal is to
reveal the information regularities, mathematically expressed by
the considered variation principle (VP), as a mathematical tool to
extractthe regularities and define the model, whichdescribes
theregularities. The IMD regularities and mechanisms are the
results of the analytical solutions and are not retained by logical
argumentation, rational introduction, and a reasonable discussion.
The IMD's information computer modeling formalism includes a human
being (as an observer, carrier and producer ofinformation), with a
restoration of the model during the objectobservations.
Informational Macrodynamics (IMD) presents the unified information
systemic approach with common information language for modeling,
analysis and optimization of a variety of interactive processes,
such as physical, biological, economical, social, and
informational, including human activities. Comparing it with
thermodynamics, which deals with transformation energy and
represents a theoretical foundation of physical technology, IMD
deals with transformation information, and can be considered a
theoretical foundation of Information Computer Technology (ICT).
ICT includes but is not limited to applied computer science,
computer information systems, computer and data communications,
software engineering, and artificial intelligence. In ICT,
information flows from different data sources, and interacts to
create new information products. The information flows may interact
physically or via their virtual connections, initiating an
information dynamic process that can be distributed in space. As in
physics, a problem is understanding general regularities of the
information processes in terms of information law, for the
engineering and technological design, control, optimization, and
development of computer technology, operations, manipulations, and
management of real information objects. Information Systems
Analysis and Modeling: An Informational Macrodynamics Approach
belongs to an interdisciplinary science that represents the new
theoretical and computer-based methodology for system informational
description and improvement, including various activities in such
interdisciplinary areas as thinking, intelligent processes,
management, and other nonphysical subjects with their mutual
interactions, informational superimpositions, and the information
transferred between interactions. Information Systems Analysis and
Modeling: An Informational Macrodynamics Approach can be used as a
textbook or secondary text in courses on computer science,
engineering, business, management, education, and psychology and as
a reference for research and industry.
Observers are everywhere, from communicating people, animals, and
different species, to any interacting subjects that accept,
transform, and exchange information.Up to now, common information
regularities, emergence, differentiation, and appearance have not
been studied through a united approach.This book presents a new
method for understanding the notion of information and its
Observers, showing how information creates Observers and generates
regularities during observation.The approach is developed from
Wheelers concept in physics, It from Bit, which has been modified
in this text to Observer-Participator Bit.Studying information
comes from probabilistic observations, emerging space-time
microprocess, entanglement, qubit, encoding bits, and evolving
macroprocess, leading to the creation of the Observer, as well as a
geometric information structure.The regularities observed
self-organize into information processes that encode information
causality, logic, and complexity, and determine the observers
cognition, evolving toward intelligence.The regularities create a
double spiral rotating coding structure, which observation
self-generates.For the first time, this book establishes the
observers united information mechanism, with self-operating
integral logic, transforming an observed uncertainty into physical
reality.The book also includes information formalism, which has
been applied to solutions for a wide range of computer science and
engineering problems implemented in practice.
The book subject is mathematical formalism, describing the creation
of the dynamic and information regularities from stochastics. The
formalism is based on the introduction of an informational path
functional, defined on trajectories of a controlled random process,
and the solution of variation problem for this novel functional.
The solution provides both the information dynamic model of a
random process and the model of optimal control. This allows
building a two-level information model with a random process at the
microlevel and a dynamic process at macrolevel. Considering a
variation principle (VP) as a mathematical form that expresses some
regularity, it is assumed that the VP extremals, represented by the
solutions of the above dynamic model, describe a movement
possessing these regularities. Such an approach has been used by R.
P. Feynman, who introduced the functional on trajectories of an
electron's movement and applied the variation principle for this
path functional to obtain the equations of quantum mechanics.
Feynman's path functional is defined on the dynamic trajectories
and has not been applied to trajectories of a random process.
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