Problems, methods and algorithms of decision making based on an uncertain knowledge now create a large and intensively developing area in the field of knowledge-based decision support systems. The main aim of this book is to present a unified, systematic description of analysis and decision problems in a wide class of uncertain systems described by traditional mathematical models and by relational knowledge representations. A part of the book is devoted to new original ideas introduced and developed by the author: the concept of uncertain variables and the idea of a learning process...

Uncertainty is one of the main features of complex and intelligent decision-making systems. There exists a great variety of definitions and descriptions of uncertain systems. The ideas of uncertain variables based on uncertain logics have been introduced and developed for a wide class of uncertain systems. In this monograph basic concepts, definitions and results concerning uncertain variables are presented. Applications to analysis and decision problems in uncertain systems, described by traditional mathematical models and by knowledge representations, are demonstrated.