Challenges in Complex Systems Science

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-defined 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.