Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular
Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems …

This interdisciplinary guide explores various types of modeling methods available for
dynamical systems. It begins with the general concepts, representations, and philosophy of …

In a parallel discrete-event simulation (PDES) scheme, tasks are distributed among
processing elements (PEs) whose progress is controlled by a synchronization scheme. For …

In financial markets, participants locally optimize their profit which can result in a globally
unstable state leading to a catastrophic change. The largest crash in the past decades is the …

Computer science and physics have been closely linked since the birth of modern
computing. In recent years, an interdisciplinary area has blossomed at the junction of these …

Complexity and complex systems are all around us: from molecular and cellular systems in
biology up to economics and human societies. There is an urgent need for methods that can …

Motivated by synchronization problems in noisy environments, we study the Edwards-
Wilkinson process on weighted uncorrelated scale-free networks. We consider a specific …

Since the sixteenth century there have been two main paradigms in the methodology of
doing science. The first one is referred to as “the experimental” paradigm. During an …

In modeling dynamic systems, one of the first questions to be answered is whether the
involved processes can be viewed to be discrete in state, time, space, or continuous. The …

Motivated by a synchronization problem in distributed computing we studied a simple growth
model on regular and small-world networks, embedded in one and two dimensions. We find …