Although the fields of synergetics and co-operative behaviour in neural systems are far from new, the last few years have seen an extraordinary growth of interest in many areas of complex systems. From ecology to economics, from particle physics to parallel computing, a new vocabulary is emerging to describe discoveries about wide-ranging and fundamental phenomena. Many of the terms have already become familiar: artificial life, biocomplexity, cellular automata, chaos, criticality, fractals, learning systems, neural networks, non-linear dynamics, parallel computation, percolation, self-organization and many more. Together they point to the emergence of new paradigms, cutting across traditional disciplines, for dealing with complex systems. One of the contributing factors to this rapid growth is the extraordinary increase in computing power over the last decade. Microprocessors have of course become much faster, but parallel computing has also come of age. Previously intractable non-linear systems are now amenable to analysis and simulation and parallel computers are ever more important in these areas.
But at a more fundamental level, we see that parallel computation is intrinsic to many natural phenomena. The papers in this volume explore many aspects of complex systems. They cover both theory and applications and deal with material drawn from many different disciplines and specialities. Throughout all the papers, however, runs the common theme of "emergent computation". Each paper deals with some aspect of this theme. The distinguishing feature of complex systems is that patterns and behaviours emerge from nonlinearities or interactions between the components. In this respect, complex systems research is inherently anti-reductionalist. The subtlety of the world we live in comes from the parallel interaction of many individuals.