Group Verbal Decision Analysis (eBook, PDF) - Petrovsky, Alexey B.
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This book describes an original approach to solving tasks of individual and collective choice: classification, ranking, and selection of multi-attribute objects. Object representation with multisets allows considering simultaneously numerical and symbolic variables. In group verbal decision analysis, judgments of all participants are taken into account without a compromise between contradictory. Natural language is used to describe problems and objects, formalize knowledge of experts and preferences of decision makers, and explain results. Verbal methods and technologies are more transparent,…mehr

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Produktbeschreibung
This book describes an original approach to solving tasks of individual and collective choice: classification, ranking, and selection of multi-attribute objects. Object representation with multisets allows considering simultaneously numerical and symbolic variables. In group verbal decision analysis, judgments of all participants are taken into account without a compromise between contradictory. Natural language is used to describe problems and objects, formalize knowledge of experts and preferences of decision makers, and explain results. Verbal methods and technologies are more transparent, less laborious for a person, and weakly sensitive to measurement errors. The book also includes examples of applying new tools in real ill-structured high-dimensional choice tasks. It is intended for researchers, managers, consultants, analysts, and developers as well as for teachers and students of applied mathematics, computer science, information processing, engineering, economics, and management.

Autorenporträt
Petrovsky Alexey B. is Professor, Doctor of Technical Sciences on System Analysis and Automated Control, Head of Department for Decision Problem, Chief Researcher, Federal Research Center “Computer Sciences and Control”, the Russian Academy of Sciences, Moscow, Russia, and Invited Professor at Moscow Physics and Technical Institute—National Research University (2004–2015), N.E. Bauman Moscow State Technical University (2006–2015), M.V. Lomonosov Moscow State University (2007–2010), Belgorod State National Research University (2010–2019), V.G. Shukhov Belgorod State Technological University (2011–2022), Volgograd State Technical University (2017-2022), Russia and graduated from M.V. Lomonosov Moscow State University (1967) and has Ph.D. degree on Theoretical and Mathematical Physics from V.A. Steklov Mathematical Institute and the USSR Academy of Sciences (1970).

Petrovsky Alexey B. is Editor-in-Chief and Member of Editorial Council, “Artificial Intelligence and Decision Making”, a journal of the Russian Academy of Sciences; Member of Editorial Boards: International Journal of Decision Support Systems, International Journal “Information Models and Analysis”, International Journal “Information Technologies and Knowledge”, “Proceedings of the Institute for Systems Analysis of the Russian Academy of Sciences”, “Strategic Decisions and Risk-Management”; a member of Editorial Council, and “Automation of Control Processes”.

Petrovsky Alexey B. is Member of the International Society on Multiple Criteria Decision Making, the European Working Group “Multiple Criteria Decision Aiding”; the Commission for working with young researchers of the Russian Academy of Sciences, the Russian Association for Artificial Intelligence; Full Member of the Russian Academy of Natural Sciences.

Petrovsky Alexey B. is Author of over 200 papers, including 7 monographs and 2 textbooks.

Research areas include discrete mathematics, multiset theory, multicriteria decision making, verbal decision analysis, decision support systems, information technologies, systems analysis, science and technology policy, R&D forecasting, and planning and management.

Rezensionen
"A book that uncovers a unique way of thinking, which we can use in the already well-known decision theory. The named methods can be found in this book for the first time, with a very nice theoretical overview and beautiful examples, followed by a detailed bibliography." (Rózsa Horváth-Bokor, zbMATH 1529.91006, 2024)