Important Dates and Information

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The most important contributions to the conference will be published in a book (Springer Proceedings in Mathematics). For selected publications of past conferences, please see the following links:

  1. http://www.springer.com/mathematics/applications/book/978-1-4419-5688-0
  2. http://www.springer.com/mathematics/applications/book/978-1-4614-3905-9
  3. http://www.amazon.com/Cooperative-Control-Optimization-Applied/dp/1402005490

Plenary Speakers

  • Dr. Roman Belavkin
    School of Engineering and Information Sciences
    Middlesex University, England
    Title: Utility, Risk and Information
    Abstract:   Mathematical theory of optimal decisions under uncertainty is based on the idea of maximisation of the expected utility functional over a set of lotteries.  This view appears natural for mathematicians, who consider these lotteries as probability measures on some common algebra of events, and linear structure of the space of measures leads to the celebrated in game theory result of von Neumann and Morgenstern about the existence of a linear or affine objective functional — the expected utility.  Behavioural economists and psychologists, on the other hand, have demonstrated that people consistently violate the axioms of expected utility, and this includes professional risk-takers such as stockbrokers.  These phenomena and paradoxes lead to the development of descriptive theories of decisions, such as the prospect theory, which uses an S-shaped ‘non-expected’ utility functional with concave and convex branches explaining respectively the risk-averse and risk-taking behaviour of human decision-makers.  Although successful in behavioural economics, these theories have not convinced mathematicians or engineers, because the non-linear properties did not follow naturally from any mathematical principles.  In this talk I will show how this non-linearity is introduced if, apart from utility, one also considers information amount that a decision-maker receives.  The utility of information is an optimal value function that is constructed by combining the expected utility and information functionals, and it has concave and convex branches corresponding precisely to those of the S-shaped function of the prospect theory.  Furthermore, we show that these properties are independent of the way the information functional is defined.  The fact that utility of information affects the optimal decision-making strategy is not only interesting for the purpose of explaining some paradoxes of behavioural economics, but it suggests that information constraints and information dynamics should be taken more broadly into account in optimisation systems and their applications.
  • Dr. My T. Thai
    Computer and Information Science and Engineering
    University of Florida
  • Dr. Viktor Zamaraev
    National Research University Higher School of Economics, Russia

Important Dates

December 15th: Early Registration
February 15th: Abstract Submission
February 15th: Late Registration

Registration Fee

Early Registration Fee: 400$
Late Registration Fee: 500$