The European Physical Journal Special Topics

, Volume 214, Issue 1, pp 245–271

Challenges in complex systems science


  • J. H. Johnson
    • Faculty of Mathematics, Computing & TechnologyThe Open University
  • J. Kertesz
    • Institute of PhysicsBudapest Univ. of Technology & Economics
  • K. Kaski
    • Dept. of Biomedical Engineering & Computational Science
  • A. Díaz-Guilera
    • Dept. Fisica FonamentalUniversitat de Barcelona
  • R. S. MacKay
    • Mathematics Institute & Centre for Complexity ScienceUniversity of Warwick
  • V. Loreto
    • Physics Dept.Sapienza Universty of Rome
    • ISI Foundation
  • P. Érdi
    • Institute for Particle and Nuclear Physics, Wigner Research Centre for PhysicsHungarian Academy of Sciences
    • Center for Complex Systems StudiesKalamazoo College
  • D. Helbing
    • ETH Zürich
Open AccessRegular Article

DOI: 10.1140/epjst/e2012-01694-y

Cite this article as:
San Miguel, M., Johnson, J.H., Kertesz, J. et al. Eur. Phys. J. Spec. Top. (2012) 214: 245. doi:10.1140/epjst/e2012-01694-y


FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda.

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© The Author(s) 2012