Granularity Helps Explain Seemingly Irrational Features of Human Decision Making -- A Comprehensive Granular Model for Decision Making with Complex Data.-Granularity in Economic Decision Making: An Interdisciplinary Review -- Decision Makers' Opinions Changing Attitude-Driven Consensus Model under Linguistic Environment and Its Application in Dynamic MAGDM -- Using Computing with Words for Managing Non-Cooperative Behaviors in Large Scale Group Decision Making -- A Type-2 Fuzzy Logic Approach for Multi-Criteria Group Decision Making -- Multi-Criteria Influence Diagrams - A Tool for the Sequential Group Risk Assessment.-Consensus Modeling under Fuzziness - A Dynamic Approach with Random Iterative Steps -- Decision Making - Interactive and Interactive Approaches -- Collaborative Decision Making by Ensemble Rule Based Classification Systems -- A GDM Method Based on Granular Computing for Academic Library Management -- Spatial-taxon Information Granules as Used in Iterative Fuzzy-Decision-Making for Image Segmentation -- Group Decision Making in Fuzzy Environment - An Iterative Procedure Based on Group Dynamics -- Fuzzy Optimization in Decision Making of Air Quality Management -- Group Decision Making in Fuzzy Environment - An Iterative Procedure Based on Group Dynamics -- Fuzzy Optimization in Decision Making of Air Quality Management.

This volume is devoted to interactive and iterative processes of decision-making- I2 Fuzzy Decision Making, in brief. Decision-making is inherently interactive. Fuzzy sets help realize human-machine communication in an efficient way by facilitating a two-way interaction in a friendly and transparent manner. Human-centric interaction is of paramount relevance as a leading guiding design principle of decision support systems.   The volume provides the reader with an updated and in-depth material on the conceptually appealing and practically sound methodology and practice of I2 Fuzzy Decision Making. The book engages a wealth of methods of fuzzy sets and Granular Computing, brings new concepts, architectures and practice of fuzzy decision-making providing the reader with various application studies.   The book is aimed at a broad audience of researchers and practitioners in numerous disciplines in which decision-making processes play a pivotal role and serve as a vehicle to produce solutions to existing problems. Those involved in operations research, management, various branches of engineering, social sciences, logistics, and economics will benefit from the exposure to the subject matter. The book may serve as a useful and timely reference material for graduate students and senior undergraduate students in courses on decision-making, Computational Intelligence, operations research, pattern recognition, risk management, and knowledge-based systems.