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may be complex without being able to be replaced by something »still more simple«. This became evident with the help of computer models of deterministic-recursive systems in which simple mathematical equation systems provide an extremely complex behavior. (2) Irregularity of nature is not treated as an anomaly but becomes the focus of research and thus is declared to be normal. One looks for regularity within irregularity. Non-equilibrium processes are recognized as the source of order and the search for equilibrium is replaced by the search for the dynamics of processes. (3) The classical system-environment model, according to which the adaptation of a system to its environment is controlled externally and according to which the adaptation of the system occurs in the course of a learning process, is replaced by a model of systemic closure. This closure is operational in so far as the effects produced by the system are the causes for the maintenance of systemic organization. If there is sufficient complexity, the systems perform internal self-observation and exert self-control (»Cognition« as understood by Maturana as self-perception and self-limitation, e. g. , that of a cell vis-a. -vis its environment). 22 But any information a system provides on its environment is a system-internal construct. The »reference to the other« is merely a special case of »self-reference«. The social sciences frequently have suffered from the careless way in which scientific ideas and models have been transferred.

This book examines the historical roots and evolution of simulation from an epistemological, institutional and technical perspective. Rich case studies go far beyond documentation of simulation’s capacity for application in many domains, they also explore the "functional" and "structural" debate that continues to traverse simulation thought and action. One here asks if simulation deeply transforms science, or instead constitutes a limited tool that principally extends the repertory of erstwhile practice. Does simulation comprise a novel form of experiment, or rather operate as a mechanism which extends standing forms of experimentation? What are simulation’s relations with models or theory, for example? These studies further query to what extent and in what ways simulation may be regarded as a discipline, a special species of instrument, or as transdisciplinary.

This book presents a broad overview of the multifaceted phenomena of innovation networks, which have assumed increasing importance with the emergence of the so-called 'knowledge economy'. The topic of innovation networks is analysed through different lenses, bringing together the theory of self-organisation, complexity theory and recent developments in the economic and sociological literature on innovation. The aim of the book is the integration of these different perspectives in order to develop a common theory of innovation networks. In this respect, a general model of innovation networks is applied to different industrial sectors such as the biotechnology industry, the telecommunications industry, and knowledge-intensive business systems which form the backbone of the internet economy. By combining empirical case studies with theoretical work on the emergence of innovation networks, the authors are able to identify the mechanisms and circumstances which can contribute to their successful development and evaluation.Innovation Networks is the result of a two year collaboration between academics from a range of different disciplines including theoretical physics, political science, computer science, sociology and economics. As such, it will appeal to students, scholars and researchers in all of these fields as well as business and R&D managers, and policymakers and politicians involved in the promotion of technology policy.

The fundamental question of whether, or in what sense, science informs us about the real world has pervaded the history of thought since antiquity. Is what science tells us about the world determined unambiguously by facts, or does the content of any scientific theory in some way depend on the human condition? "Sokals hoax" attacked the mere seriousness of post-modern views of science and shifted this controversial debate to a new level, which very quickly came to be known as "Science Wars". "Knowledge and the World" examines and reviews the broad range of philosophical positions on this issue, extending from realism to relativism, to expound the epistemic merit of t science, and to tackle the central question: in what sense can science justifiably claim to provide a truthful portrait of reality? Challenges beyond the Science Wars are taken up by contributions of scientists, sociologists and philosophers of science, which connect perspectives of a wide variety of disciplines (including biology and cultural studies). This book addresses everyone interested in the philosophy and history of science, and in particular in the interplay between the social and natural sciences.

The fundamental question of whether, or in what sense, science informs us about the real world has pervaded the history of thought since antiquity. Is what science tells us about the world determined unambiguously by facts, or does the content of any scientific theory in some way depend on the human condition? "Sokal’s hoax" attacked the mere seriousness of post-modern views of science and shifted this controversial debate to a new level, which very quickly came to be known as "Science Wars"."Knowledge and the World" examines and reviews the broad range of philosophical positions on this issue, extending from realism to relativism, to expound the epistemic merit of t science, and to tackle the central question: in what sense can science justifiably claim to provide a truthful portrait of reality? Challenges beyond the Science Wars are taken up by contributions of scientists, sociologists and philosophers of science, which connect perspectives of a wide variety of disciplines (including biology and cultural studies). This book addresses everyone interested in the philosophy and history of science, and in particular in the interplay between the social and natural sciences.

may be complex without being able to be replaced by something »still more simple«. This became evident with the help of computer models of deterministic-recursive systems in which simple mathematical equation systems provide an extremely complex behavior. (2) Irregularity of nature is not treated as an anomaly but becomes the focus of research and thus is declared to be normal. One looks for regularity within irregularity. Non-equilibrium processes are recognized as the source of order and the search for equilibrium is replaced by the search for the dynamics of processes. (3) The classical system-environment model, according to which the adaptation of a system to its environment is controlled externally and according to which the adaptation of the system occurs in the course of a learning process, is replaced by a model of systemic closure. This closure is operational in so far as the effects produced by the system are the causes for the maintenance of systemic organization. If there is sufficient complexity, the systems perform internal self-observation and exert self-control (»Cognition« as understood by Maturana as self-perception and self-limitation, e. g. , that of a cell vis-a. -vis its environment). 22 But any information a system provides on its environment is a system-internal construct. The »reference to the other« is merely a special case of »self-reference«. The social sciences frequently have suffered from the careless way in which scientific ideas and models have been transferred.