Decision Synthesis
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Decision Synthesis
Author: Stephen R. Watson
language: en
Publisher: Cambridge University Press
Release Date: 1987
Offers a comprehensive overview of the theory of decision making and its practical application in decision analysis.
Modeling Decisions for Artificial Intelligence
This book constitutes the refereed proceedings of the 18th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2021, held in Umeå, Sweden, in September 2021.* The 24 papers presented in this volume were carefully reviewed and selected from 50 submissions. Additionally, 3 invited papers were included. The papers discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making; approximate reasoning; machine learning; data science and data privacy. *The conference was held virtually due to the COVID-19 pandemic.
Executive Decision Synthesis
This book provides a practice-driven, yet rigorous approach to executive management decision-making that performs well even under unpredictable conditions. It explains how executives can employ prescribed engineering design methods to arrive at robust outcomes even when faced with uncontrollable uncertainty. The book presents the paradigm and its main principles in Part I; in Part II it illustrates how to frame a decision situation and how to design the decision so that it will produce its intended behavior. In turn, Part III discusses in detail in situ case studies on executive management decisions. Lastly, Part IV summarizes the book and formulates the key lessons learned.