Decision Making and Imperfection

  • Tatiana V. Guy
  • Miroslav Karny
  • David Wolpert

Part of the Studies in Computational Intelligence book series (SCI, volume 474)

Table of contents

  1. Front Matter
    Pages 1-13
  2. Edwin Simpson, Stephen Roberts, Ioannis Psorakis, Arfon Smith
    Pages 1-35
  3. Joong Bum Rhim, Lav R. Varshney, Vivek K. Goyal
    Pages 37-63
  4. Ritchie Lee, David H. Wolpert, James Bono, Scott Backhaus, Russell Bent, Brendan Tracey
    Pages 101-128
  5. Marina Fiori, Alessandra Lintas, Sarah Mesrobian, Alessandro E. P. Villa
    Pages 129-161
  6. Javier G. Rázuri, Pablo G. Esteban, David Ríos Insua
    Pages 163-187

About this book


Decision making (DM) is ubiquitous in both natural and artificial systems. The decisions made often differ from those recommended by the axiomatically well-grounded normative Bayesian decision theory, in a large part due to limited cognitive and computational resources of decision makers (either artificial units or humans). This state of a airs is often described by saying that decision makers are imperfect and exhibit bounded rationality. The neglected influence of emotional state and personality traits is an additional reason why normative theory fails to model human DM process.


The book is a joint effort of the top researchers from different disciplines to identify sources of imperfection and ways how to decrease discrepancies between the prescriptive theory and real-life DM. The contributions consider:


·          how a crowd of imperfect decision makers outperforms experts' decisions;


·          how to decrease decision makers' imperfection by reducing knowledge available;


·          how to decrease imperfection via automated elicitation of DM preferences;


·          a human's limited willingness to master the available decision-support tools as an additional source of imperfection;


·          how the decision maker's emotional state influences the rationality;  a DM support of edutainment robot based on its system of values and respecting emotions.


The book will appeal to anyone interested in the challenging topic of DM theory and its applications.



Computational Intelligence Decision Making Imperfection

Editors and affiliations

  • Tatiana V. Guy
    • 1
  • Miroslav Karny
    • 2
  • David Wolpert
    • 3
  1. 1.Theory and Automation, Academy of SciencesInstitute of InformationPragueCzech Republic
  2. 2.and Automation, Academy of SciencesInstitute of Information TheoryPragueCzech Republic
  3. 3.Los Alamos National LaboratoryLos AlamosUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-36405-1
  • Online ISBN 978-3-642-36406-8
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences