Complex dynamical systems of many interacting units are characterized by emergent global properties. These properties can be tuned by microscopic "rules of attraction" among individual units. Networks (or mathematical graphs) have proved as useful conceptual representations of the interactions in the extended dynamical systems, and
in particular, networks have provided the theoretical background for the

*quantitative study* of both structure and dynamical effects in complex systems. In recent years scientists have recognized that many networks representing real dynamical systems in physics, biology, economics, and in other disciplines, have a complex structure, which requires new mathematical approaches. The reasons for this structural complexity
may be found in the fact that the basic units in these systems are physical objects (agents) with various properties, which in general determine the nature of "linking" in the network models. In addition, these properties may vary in time, hence leading to the temporal development of the structure, that includes

*self-organization, competition and constraints.*
The workshop

**Networks, Complexity & Competition** will focus on the quantitative study of complex dynamical systems, primarily using concepts developed in the network theory, and applications of these concepts in econo-physics, bio-informatics, nano-sciences and social sciences.

The Workshop is a part of the COST P10 Action "Physics of Risk".