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On Support of Imperfect Bayesian Participants

  • Miroslav Kárný
  • Tatiana V. Guy
Part of the Intelligent Systems Reference Library book series (ISRL, volume 28)

Abstract

Bayesian decision theory provides a strong theoretical basis for a single-participant decision making under uncertainty, that can be extended to multiple-participant decision making. However, this theory (similarly as others) assumes unlimited abilities of a participant to probabilistically model the participant’s environment and to optimise its decision-making strategy. The proposed methodology solves knowledge and preference elicitation, as well as sharing of individual, possibly fragmental, knowledge and preferences among imperfect participants. The approach helps to overcome the non-realistic assumption on participants’ unlimited abilities.

Keywords

Decision Making Decision Making Task Decision Making Strategy Preference Elicitation Decision Making Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Miroslav Kárný
    • 1
  • Tatiana V. Guy
    • 1
  1. 1.Institute of Information Theory and AutomationAcademy of Sciences of the Czech RepublicPrague 8Czech Republic

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