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.