Data processing has become essential to modern civilization. The original data for this processing comes from measurements
or from experts, and both sources are subject to uncertainty. Traditionally, probabilistic methods have been used to process
uncertainty. However, in many practical situations, we do not know the corresponding probabilities: in measurements, we often
only know the upper bound on the measurement errors; this is known as interval uncertainty. In turn, expert estimates often
include imprecise (fuzzy) words from natural language such as "small"; this is known as fuzzy uncertainty. In this book, leading
specialists on interval, fuzzy, probabilistic uncertainty and their combination describe state-of-the-art developments in
their research areas. Accordingly, the book offers a valuable guide for researchers and practitioners interested in data processing
under uncertainty, and an introduction to the latest trends and techniques in this area, suitable for graduate students.