Innovation Networks; New Approaches in Modelling and Analyzing

Abstract

Springer Complexity is an interdisciplinary program publishing the best research and academic-level teaching on both fundamental and applied aspects of complex systems – cutting across all traditional disciplines of the natural and life sciences, engineering, economics, medicine, neuroscience, social and computer science. Complex Systems are systems that comprise many interacting parts with the abil-ity to generate a new quality of macroscopic collective behavior the manifestations of which are the spontaneous formation of distinctive temporal, spatial or functional structures. Models of such systems can be successfully mapped onto quite diverse " real-life " situations like the climate, the coherent emission of light from lasers, chemical reaction-diffusion systems, biological cellular networks, the dynamics of stock markets and of the internet, earthquake statistics and prediction, freeway traf-fic, the human brain, or the formation of opinions in social systems, to name just some of the popular applications. Although their scope and methodologies overlap somewhat, one can distinguish the following main concepts and tools: self-organization, nonlinear dynamics, syn-ergetics, turbulence, dynamical systems, catastrophes, instabilities, stochastic pro-cesses, chaos, graphs and networks, cellular automata, adaptive systems, genetic al-gorithms and computational intelligence. The two major book publication platforms of the Springer Complexity program are the monograph series " Understanding Complex Systems " focusing on the vari-ous applications of complexity, and the " Springer Series in Synergetics " , which is devoted to the quantitative theoretical and methodological foundations. In addition to the books in these two core series, the program also incorporates individual titles ranging from textbooks to major reference works.