This book introduces a new set of practical principles for eliminating and reducing risk in any kind of system, whether financial or non financial and including engineering, computer and business systems -- and even military systems.
Although these new principle have come from research into risk in engineering and computer systems, surprisingly, they also resolve an old dispute in the investment arena, between the academic theorists who use the beta measure of risk and the followers of the ideas of the late Benjamin Graham, and his famous disciple, Warren Buffett. Each side is well known for castigating the theories and ideas of the other, with seemingly little common ground.
The new risk principles, and principles for eliminating risk, show clearly that both sides in this famous dispute are right, for the new principles bridge the gap between the two. They show that the beta-theory proponents simply had failed to develop their theory far enough -- their risk measure in particular -- to include risk elimination possibilities.
At the heart of the new theory of risk in systems are two ideas: first, the idea of extending the risk measure to include average system output loss with respect to the best-case system output, and second, the idea of eliminating those output losses with respect to the best case, thus preserving the benefit of running the risk.
The author presents the new principles along with many practical and numerical examples, and the essential ideas are clearly explained. Nevertheless, if you examine the material closely, you will find that it will withstand a rigorous analysis.
There are some elementary mathematical relationships in the book, but because their meaning is also well explained in words, and reinforced by practical examples, these can often be skipped. The intent is to enable you to grasp the ideas and concepts well enough to enable you to put them to practical use, in whatever your field of endeavor, anything from spacecraft engineering, to computer systems design, to investment management.
In The Emerging Consensus of Social Systems Theory Bausch summarizes the works of over 30 major systemic theorists. He then goes on to show the converging areas of consensus among these out-standing thinkers.
Bausch categorizes the social aspects of current systemic thinking as falling into five broadly thematic areas: designing social systems, the structure of the social world, communication, cognition and epistemology.
These five areas are foundational for a theoretic and practical systemic synthesis. They were topics of contention in a historic debate between Habermas and Luhmann in the early 1970's. They continue to be contentious topics within the study of social philosophy.
Since the 1970's, systemic thinking has taken great strides in the areas of mathematics, physics, biology, psychology, and sociology. This book presents a spectrum of those theoretical advances. It synthesizes what various strains of contemporary systems science have to say about social processes and assesses the quality of the resulting integrated explanations.
Bausch gives a detailed study of the works of many present-day systems theorists, both in general terms, and with regard to social processes. He then creates and validates integrated representations of their thoughts with respect to his own thematic classifications. He provides a background of systemic thinking from an historical context, as well as detailed studies of developments in sociological, cognitive and evolutionary theory. This book presents a coherent, dynamic model of a self-organizing world. It proposes a creative and ethical method of decision-making and design. It makes explicit the relations between structure and process in the realms of knowledge and being. The new methodology that evolves in this book allows us to deal with enormous complexity, and to relate ideas so as to draw out previously unsuspected conclusions and syntheses. Therein lies the elegance and utility of this model.
Comprehension of complex systems comes from an understanding of not only the behavior of constituent elements but how they act together to form the behavior of the whole. However, given the multidisciplinary nature of complex systems, the scattering of information across different areas creates a chaotic situation for those trying to understand possible solutions and applications.
Modeling and Control of Complex Systems brings together a number of research experts to present some of their latest approaches and future research directions in a language accessible to system theorists. Contributors discuss complex systems such as networks for modeling and control of civil structures, vehicles, robots, biomedical systems, fluid flow systems, and home automation systems. Each chapter provides theoretical and methodological descriptions of a specific application in the control of complex systems, including congestion control in computer networks, autonomous multi-robot docking systems, modeling and control in cancer genomics, and backstepping controllers for stabilization of turbulent flow PDEs.
With this unique reference, you will discover how complexity is dealt with in different disciplines and learn about the latest methodologies, which are applicable to your own specialty. The balanced mix of theory and simulation presented by Modeling and Control of Complex Systems supplies a strong vehicle for enlarging your knowledge base a fueling future advances and incredible breakthroughs.