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Decision Science: A Human-Oriented Perspective [electronic resource] / by George Mengov.

By: Mengov, George [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Intelligent Systems Reference Library: 89Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015Description: XVIII, 160 p. 33 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783662471227.Subject(s): Engineering | Operations research | Decision making | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics) | Operation Research/Decision TheoryAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
PART I: Subjective Utility -- PART II: Psychological Insights -- PART III: Intuition and Decisions.
In: Springer eBooksSummary: This book offers a new perspective on human decision-making by comparing the established methods in decision science with innovative modelling at the level of neurons and neural interactions. The book presents a new generation of computer models, which can predict with astonishing accuracy individual economic choices when people make them by quick intuition rather than by effort. A vision for a new kind of social science is outlined, whereby neural models of emotion and cognition capture the dynamics of socioeconomic systems and virtual social networks. The exposition is approachable by experts as well as by advanced students. The author is an Associate Professor of Decision Science with a doctorate in Computational Neuroscience, and a former software consultant to banks in the City of London.  .
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PART I: Subjective Utility -- PART II: Psychological Insights -- PART III: Intuition and Decisions.

This book offers a new perspective on human decision-making by comparing the established methods in decision science with innovative modelling at the level of neurons and neural interactions. The book presents a new generation of computer models, which can predict with astonishing accuracy individual economic choices when people make them by quick intuition rather than by effort. A vision for a new kind of social science is outlined, whereby neural models of emotion and cognition capture the dynamics of socioeconomic systems and virtual social networks. The exposition is approachable by experts as well as by advanced students. The author is an Associate Professor of Decision Science with a doctorate in Computational Neuroscience, and a former software consultant to banks in the City of London.  .

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