Dynamic Decision Behavior and Optimal Guidance Through Information Services: Models and Experiments

  • Dirk Helbing
Conference paper


In this contribution, dynamical models for decision making with and without temporal constraints are developed and applied to opinion formation, migration, game theory, the self-organization of behavioral conventions, etc. These models take into account the non-transitive and probabilistic aspects of decisions, i.e. they reflect the observation that individuals do not always take the decision with the highest utility or payoff. We will also discuss issues like the freedom of decision making, the red-bus-blue-bus problem, and effects of pair interactions such as the transition from individual to mass behavior.

In the second part, the theory is compared with recent results of experimental games relevant to the route choice behavior of drivers. The adaptivity (“group intelligence”) with respect to changing environmental conditions and unreliable information is very astonishing. Nevertheless, we find an intermittent dynamical reaction to aggregate information similar to volatility clustering in stock market data, which leads to considerable losses in the average payoffs. It turns out that the decision behavior is not just driven by the potential gains in payoffs. To understand these findings, one has to consider reinforcement learning, which can also explain the empirically observed emergence of individual response patterns. Our results are highly significant for predicting decision behavior and reaching the optimal distribution of behaviors by means of decision support systems. These results are practically relevant for any information service provider.


Test Person Route Choice User Equilibrium Decision Behavior Transportation Research Record 
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 2004

Authors and Affiliations

  • Dirk Helbing
    • 1
    • 2
    • 3
  1. 1.Institute for Economics and Traffic, Faculty of Traffic Sciences “Friedrich List”Dresden University of TechnologyDresdenGermany
  2. 2.Collegium Budapest — Institute for Advanced StudyBudapestHungary
  3. 3.CCM—Centro de Ciências MatemáticasUniversidade da Madeira, Campus Universitário da PenteadaFunchal, MadeiraPortugal

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