Why Deep Neural Networks: A Possible Theoretical Explanation.- From Global to Local Constraints: A Constructive Version of Bloch's Principle -- Algebraic Product is the Only t-Norm for Which Optimization Under Fuzzy Constraints is Scale-Invariant.- Automatic Loop-shaping of H ͚/μ problem in QFT using Interval Consistency based Hybrid Optimization.- Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint -- Dow Theory's Peak-and-Trough Analysis Justified.

This book describes new algorithms and ideas for making effective decisions under constraints, including applications in control engineering, manufacturing (how to optimally determine the production level), econometrics (how to better predict stock market behavior), and environmental science and geosciences (how to combine data of different types). It also describes general algorithms and ideas that can be used in other application areas. The book presents extended versions of selected papers from the annual International Workshops on Constraint Programming and Decision Making (CoProd'XX) from 2013 to 2016. These workshops, held in the US (El Paso, Texas) and in Europe (Würzburg, Germany, and Uppsala, Sweden), have attracted researchers and practitioners from all over the world. It is of interest to practitioners who benefit from the new techniques, to researchers who want to extend the ideas from these papers to new application areas and/or further improve the corresponding algorithms, and to graduate students who want to learn more - in short, to anyone who wants to make more effective decisions under constraints.