Regular Article

The European Physical Journal Special Topics

, Volume 214, Issue 1, pp 245-271

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Challenges in complex systems science

  • M. San MiguelAffiliated withIFISC (CSIC-UIB) Email author 
  • , J. H. JohnsonAffiliated withFaculty of Mathematics, Computing & Technology, The Open University
  • , J. KerteszAffiliated withInstitute of Physics, Budapest Univ. of Technology & Economics
  • , K. KaskiAffiliated withDept. of Biomedical Engineering & Computational Science
  • , A. Díaz-GuileraAffiliated withDept. Fisica Fonamental, Universitat de Barcelona
  • , R. S. MacKayAffiliated withMathematics Institute & Centre for Complexity Science, University of Warwick
  • , V. LoretoAffiliated withPhysics Dept., Sapienza Universty of RomeISI Foundation
  • , P. ÉrdiAffiliated withIFISC (CSIC-UIB)Institute for Particle and Nuclear Physics, Wigner Research Centre for Physics, Hungarian Academy of SciencesCenter for Complex Systems Studies, Kalamazoo College
  • , D. HelbingAffiliated withIFISC (CSIC-UIB)ETH Zürich


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.

Graphical abstract