Decision Making: Uncertainty, Imperfection, Deliberation and Scalability

  • Tatiana V. Guy
  • Miroslav Kárný
  • David H. Wolpert

Part of the Studies in Computational Intelligence book series (SCI, volume 538)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Pablo G. Esteban, David Ríos Insua
    Pages 33-53
  3. Miroslav Kárný, Tatiana V. Guy
    Pages 55-89
  4. Kateřina Hlaváčková-Schindler, Sergiy Pereverzyev Jr.
    Pages 91-117
  5. Dietlind Zühlke, Gernoth Grunst, Kerstin Röser
    Pages 119-144
  6. Sarah K. Mesrobian, Michel Bader, Lorenz Götte, Alessandro E. P. Villa, Alessandra Lintas
    Pages 145-184

About this book

Introduction

This volume focuses on uncovering the fundamental forces underlying dynamic decision making among multiple interacting, imperfect and selfish decision makers.

The chapters are written by leading experts from different disciplines, all considering the many sources of imperfection in decision making, and always with an eye to decreasing the myriad discrepancies between theory and real world human decision making.

Topics addressed include uncertainty, deliberation cost and the complexity arising from the inherent large computational scale of decision making in these systems.

In particular, analyses and experiments are presented which concern:

• task allocation to maximize “the wisdom of the crowd”;

• design of a society of “edutainment” robots who account for one anothers’ emotional states;

• recognizing and counteracting seemingly non-rational human decision making;

• coping with extreme scale when learning causality in networks;

• efficiently incorporating expert knowledge in personalized medicine;

• the effects of personality on risky decision making.

The volume is a valuable source for researchers, graduate students and practitioners in machine learning, stochastic control, robotics, and economics, among other fields.

Keywords

Computational Intelligence Decision Making Scalability Scalable Decision Making Uncertainty Imperfection Deliberation

Editors and affiliations

  • Tatiana V. Guy
    • 1
  • Miroslav Kárný
    • 2
  • David H. Wolpert
    • 3
  1. 1.Institute of Information Theory and AutomationThe Czech Academy of SciencesPragueCzech Republic
  2. 2.Institute of Information Theory and AutomationThe Czech Academy of SciencesPragueCzech Republic
  3. 3.Santa Fe InstituteSanta FeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-15144-1
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-15143-4
  • Online ISBN 978-3-319-15144-1
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book