Complex Systems and Cellular Automata Models in the Study of Complexity

Abstract

Complex systems consist of a large number of interconnected and mutually interacting components. The real world is full of examples of complex adaptive systems from ancient and modern cultures, biological and social systems to economies and ecosystems. The study of complex systems is crucial for a constructive assessment and understanding of essential aspects of everyday life. Computational approaches to the analysis of complexity are among the most important tools used for this purpose. The current paper aims to offer an overview of complex systems and their main properties of emergence, adaptability and self-organization. Cellular automata are reviewed as major computational techniques engaged for complex systems modelling. In a cellular automaton, simple rules give rise to complex emergent behaviours worth investigated in the context of many real-world complex models. Perspectives of promising research directions to be tackled are discussed. <br />