Overview
- Recent research on Human-Centric Decision-Making Models for Social Sciences
- Presents Computational Intelligence models for Social Sciences
- Written by leading experts in the field
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 502)
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About this book
The volume delivers a wealth of effective methods to deal with various types of uncertainty inherently existing in human-centric decision problems. It elaborates on comprehensive decision frameworks to handle different decision scenarios, which help use effectively the explicit and tacit knowledge and intuition, model perceptions and preferences in a more human-oriented style.
The book presents original approaches and delivers new results on fundamentals and applications related to human-centered decision making approaches to business, economics and social systems. Individual chapters cover multi-criteria (multiattribute) decision making, decision making with prospect theory, decision making with incomplete probabilistic information, granular models of decision making and decision making realized with the use of non-additive measures. New emerging decision theories being presented as along with a wide spectrum of ongoing research make the book valuable to all interested in the field of advanced decision-making. The volume, self-contained in its nature, offers a systematic exposure to the concepts, design methodologies, and detailed algorithms. A prudent balance between the theoretical studies and applications makes the material suitable for researchers and graduate students in information, computer sciences, psychology, cognitive science, economics,system engineering, operation research and management science, risk management, public and social policy.
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Keywords
Table of contents (17 chapters)
Editors and Affiliations
Bibliographic Information
Book Title: Human-Centric Decision-Making Models for Social Sciences
Editors: Peijun Guo, Witold Pedrycz
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-642-39307-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2014
Hardcover ISBN: 978-3-642-39306-8Published: 13 November 2013
Softcover ISBN: 978-3-662-51069-8Published: 27 August 2016
eBook ISBN: 978-3-642-39307-5Published: 01 November 2013
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: VIII, 418
Number of Illustrations: 79 b/w illustrations
Topics: Computational Intelligence, Artificial Intelligence, Social Sciences, general