This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers

Reports on cutting-edge methods, with an emphasis on soft computing for decision-making Highlights advanced concepts, such as dynamic consensus modeling Discusses novel ways to analyze imprecise information in a wide range of research areas, from psychology to economic and political science Includes supplementary material: sn.pub/extras

Inhalt
Optimal Group Decision Making Can Help Decrease Poverty, Inequality, and Discrimination.- An Overview and Re-Interpretation of Paradoxes of Responsiveness.- Veto in Yes-no and Yes-no-abstain Voting Systems.- Power Indices for Finance.- The binomial decomposition of the single parameter family of GB welfare functions.- The logic of information and processes in the system-of-systems applications.- Decision-making Process using Hyperstructures and Fuzzy Structures in the Social Sciences.- Social Preferences through Riesz Spaces: A First Approach.- Coherent conditional plausibility: a tool for handling fuzziness and uncertainty under partial information.- Intuitionistic fuzzy interpretations of some formulas for estimation of preference degree.- Fuzzified Likert Scales in Group Multiple-criteria Evaluation.- Maximal Entropy and Minimal Variability OWA Operator Weights: A Short Survey of Recent Developments.