This book, written by leading Bulgarian specialists in. Decision making, presents a new approach to the adaptive mathematical modeling of complex systems, ...
Decision Control, Management, and Support in Adaptive and Complex Systems FOREWORD
This book, written by leading Bulgarian specialists in Decision making, presents a new approach to the adaptive mathematical modeling of complex systems, in which human knowledge is decisive to achieve the best result. As it is widely appreciated now, the human thinking and preferences have quantitative nature that makes the decision making problems in complex systems to be considered as quantitative due to the difficulties or even impossibility for qualitative description. The methods presented in the book are appropriate for decision making when scarce information is available, especially in the initial development phase of complex problems and situations. The main direction of the presentation is toward the branch of model driven Decision making, Value-driven design and Value-based Management as crucial aspects of model driven design. The subject area of the book addresses theory of measurement (scaling), utility theory and Bayesian approach in decision making theory, stochastic approximation and potential function method, machine learning and optimal control theory. The representation of complex systems using utility function as objective function needs mathematical tools for evaluation of this function on the basis of qualitative human information. The utility evaluation is a stochastic procedure developed like machine learning approach and permits development of information and decision support of systems based on mathematically grounded solutions. This approach together with the classical application of control theory ensures control solutions with mathematical exactness in regard to complex systems with human participation and permits a new point of view for development of information systems for individual utility assessment. Some important ways of applications are given in practical cases of model driven design and optimal control in biotechnology, value based management in bird prediction and e-learning personalization. The book reflects the author’s opinion that the mathematical proofs are necessary to be provided in details for readers/scholars with mathematical background and sufficiently serious mathematical experience. In that way they could study in depth the outlined principles and methods and eventually further develop some of them.
The book has a monographic character and includes theoretical results as well as practical applications of scientific research carried out by the authors in Bulgarian Academy of Sciences during the previous three decades. It provides a general mathematical paradigm as well as many numerical methods suitable for implementation by practitioners constructing Value models in new applications in different important areas such as sociology, medicine, agriculture, control design and economics. The references contain carefully chosen fundamental bibliographic sources that may be consulted in case of deeper investigation. In this way the book could be useful for researchers and scholars working in the fields where the quantitative decision making is applied. Reading of the book requires some basic mathematic knowledge about sets, relations and operations over them. The practitioners could omit the proofs of the theorems and could follow only the examples of applications of the mathematical methods. They could follow, based on these examples, the ways of development of Value driven modeling and models in the different chapters. That is why, as the authors stress, the book is not a simple collection of value driven models in different areas of human activity, but guidance how to design value driven models and how to perform value driven decision making in complex processes. The book can supplement upper-level courses and postgraduate courses and it can serve decision makers as a valuable resource for designing complex systems.
