Background

Long after the discovery of atoms and molecules it was still customary in science to think about a collection ofmany similar objects in terms of some “representative individual” endowed with the sum, or average of their individual properties. It was as if, in spite of the discovery of the discrete structure and its capability to induce dramatic phase transitions, many scientists felt that the potential for research and results within the continuum / linear framework has not been exhausted and insisted to go on with its study. For another hundred of years, the established sciences were able to progress within this conceptual framework.

In fact, one may argue that this “mean field” / continuum / linear way of thinking is what conserved the classical sciences as independent sub-cultures. Indeed, it is exactly when these assumptions do not hold that the great conceptual jumps separating between the various sciences arise.

When "More Is Different" life emerges from chemistry, chemistry from physics, conscience from life, social conscience/ organization from individual conscience etc.

Similarly, the emergence of complexity takes place in human created artifacts: collections of simple instructions turn into a complex distributed software environment, collections of hardware elements turn into a world wide network, collections of switches / traffic lights turn into communication / traffic systems etc.

This study of the emergence of new collective properties qualitatively different from the properties of the “elementary” components of the system breaks the traditional boundaries between sciences: the “elementary” objects belong to one science - say chemistry - while the collective emergent objects to another one - say biology. For lack of other terms (and in spite of many objections that can be advanced) we will call below the science to which the “elementary” objects belong - the “simpler” science while the science to which the emergent collective objects belong will be called the “more complex” science. As for the methods, they fall “in between”: in the “interdisciplinary space”. The ambitious challange of the Complexity community (its “manifest destiny”) is prospecting, mapping, colonizing and developing this “interdisciplinary” territory.

It is not by chance that the initial reaction to this enterprise was not very enthusiastic: the peers in the “simpler” science recognized the complexity objective (explaining the emergence and properties of the “more complex” science) as strange to its own endeavor. The peers in the “target”, “more complex” field felt that the basic concepts (the elements from the “simpler science”) are strange to the conceptual basis of their discipline (and too far away from its observable phenomenology). And all together felt that the very problematics and methods proposed by Complexity are not faithful to the classical way of making and dividing science.

In the case of the electronic and software artifacts, the “more complex” science is not defined as such to this very day. The naïve (and probably wrong) assumption is that the scientists responsible for it are and should be the people in charge with the elementary artifacts (computer scientists and electronic engineers). In the case in which the elementary objects are humans, the situation can be further complicated / complexified. Indeed, in this case, their behavior can be influenced by their recognition of the collective emergent (social) objects as such. This is a final blow to even neo-reductionist thinking, as the emergent “more complex” level becomes explicitly and directly an actor in the “simpler” individuals dynamics.

Fortunately an increasing number of scientific leaders and many young students find the challenge of Complexity crucial for further progress not only in pure science but also in understanding and mastering the most of our daily experience. In the last years this claim is being more and more substantiated.

In conclusion:

- The Complexity community has in addition to its intrinsic interdisciplinary character a common problematics and methodology.

- It carries the potential for synthesizing a large portion of reality into a well defined and integrated discipline.

- Supporting Complexity is scientifically and socially justified.

- The support has to be awarded to Complexity as such: there is no hope that funds allocated to the classical fields will end up being used for the advancement of Complexity.

History and Goals

Given the evident potential of the science of complex systems and because of the increasing problems, e.g., in the management of complex electronic or software systems, and in the control of political and economic networks, various bodies, institutions and governments have acted to strengthen the research in complexsystems and to foster the transfer of knowledge.
Such programs are NEST (New and Emergent Science and Technology) and IST-FET (Information Society Technology - Future and Emerging Technologies) in EU and the Center for Complexity Science in Jerusalem. Significant investments have been made to support new fields of research such as networks, cognitive systems, artificial cells, autonomously interacting robots, and many other areas. Two coordination actions were particularly effective in centralizing the activity of the many complexity projects: GIACS and ONCE-CS .
One of the main results of this investment was a series of conferences: Turin 2004 , Paris 2005 , Oxford 2006 and Dresden 2007 with the result of bringing together the various related disciplines, focusing the diverse research activities, and fostering them. The goal of the 2008 conference in Jerusalem is to reflect the recent progress in the field of complexity science and to significantly increase the actively involved community.