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A review of the studies on institutional complexity reveals that the many definitions of institutional complexity and related concepts share similarities with the understanding of complexity and complex systems of complexity science. Yet few publications on institutional complexity engage explicitly with complexity science. Most observers still confuse complicated and complex systems, for instance. Furthermore, the variety of definitions may create disarray regarding what institutional complexity and its related concepts are and what they imply. Highlighting the similarities between institutional complexity and complexity science in global governance, this think piece offers a conceptual and operational definition of institutional complexity using a complexity science lens. It highlights the attributes and properties of institutional complexity. It also presents the benefits of such an approach. Besides offering advantages in terms of concept clarification, this approach aims to engage theoretically, epistemologically, and methodologically with the complexity of global governance, as well as propose a way to answer remaining questions on this crucial topic.

To banish the complex to the periphery of knowledge is becoming increasingly impossible in all the sciences--except in the human sciences where the trend towards reductiveness could very well express the sense of loss experienced in the face of the most complex subject-matter of all. In contrast to even the most highly perfected artificial automaton, the most rudimentary natural automaton, (let alone the yet more complex living system of man & his society), possesses a complexity which can no longer be captured by systems theory & cybernetics. The functioning of the natural living system does not depend on the high reliability of its component parts or on the immediate suppression of disorder, 'noise' & error, but, on the contrary, needs some degeneration of its component parts & is consistent with some disorder, 'noise' & error. The more highly a living system is in fact evolved, the more it will comprise of disorder, & error, for it is from that disorder (whether due to deterioration, conflict, or antagonism) that its ability to adapt to new conditions, to generate a newer & better organization of itself out of itself, follows. Thus biological complexity results in generativity, but also generativity, by enriching the hereditary stock by adding to its complexity (by means of favorable genetic mutations) produces further ramification of self-organization, ie further complexity. A logic, which can capture this paradox of the generativity of living systems depending on the very unreliability & degenerativity of their component parts, of 'life from death, death from life', must pass beyond a Manichaen opposition between 2 antagonistic principles to a logic of complexity marked by 'the absence of pervasive rigid categories'. In this logic the binary logic of all or nothing is sublated, in the Hegelian sense, in a richer logic which can deal with imprecise objects, 'fuzzy sets', in an uncertain & oscillatory way. Von Foerster's 'dialogic', as the symbiotic combination of 2 types of logic (the digital & the analogical), might be seen to adequately reflect the symbiotic combination of the unstable, metamorphic, metabolic logical principle of life (in the proteinic phenomenal system) & the constant self-perpetuating logic of the generative system (DNA). This symbiosis produced by such a 'dialogic' is itself complex, as it not only nullifies competing & antagonistic features but also integrates & uses them for vital purposes in a manner which eludes rationalization & is therefore, from the standpoint of our (Aristotelian) logic, absurd. Hegel's dialectical logic, though ignoring the essential part played in 'becoming' by chance, brought out the enantiomorphous dialectic of living systems in its stress on the positive character of negativity arising from the negation of negation, captured also by the term 'negentropy' which, needing entropy (itself the negation of complex order) to build a still more complex order, is the negation of that negation. The logic of living things, in contrast to Aristotelian logic, is not tautological but generative, nonlinear, & arborescent like evolution, opening out onto the probabilistic, the ambiguous, the aberrant, the imaginative, the creative. K. Schmitt.

The last fifteen or twenty years have been marked by fundamental advances in the sources of complex behavior in micro- and macro-economics, in the practical and methodological implications of such behavior, and in the methods and tools appropriate to cope with them. Much of these developments have been driven by the recognition and acceptance by economists of approaches initiated in other fields - such as non-linear dynamics, statistical physics, network theory, biology, computer science, and the use of computational methods as problem-solving tools - giving rise to important and innovative impulses to economic thinking. The sixteen papers in this book -- the fourteenth volume in the series International Symposia in Economic Theory and Econometrics - reflect from various perspectives this recent evolution. They are the outgrow from a selection of communications presented at the COMPLEXITY2000 workshop held in Aix en Provence, France, 4-6 May 2000 - a workshop that brought together, from twenty-two nations, almost seventy economists, mathematicians, biologists and physicists interested in complex phenomena. All papers were strictly refereed in the intended tradition of the series: to provide journal quality collections of research papers of unusual importance in areas of currently highly visible activity within the economics profession. With its selection of articles, the book presents an overview of advanced contributions to complexity in economics and social system, such as chaotic dynamics and multiple equilibria, agent-based models, applications of genetic algorithms, non-equilibrium macro-dynamics, information transmission, learning mechanisms. Although the papers address economic problems, the authorship and the perspectives presented are interdisciplinary and provide therefore a number of innovative insights and solutions to classical or new questions

We develop the ontology of "process complexity" and describe how the dynamics of "becoming" can be framed as the emerging, stabilising, and ultimate dissolving of "patterns of relationships." By extending traditional complexity thinking through introducing a "field theory" view, we develop a more nuanced and inclusive perspective of the processual complex world. We show how this leads to the idea of ontological uncertainty. We demonstrate how process complexity resonates with the ontologies of many different schools of thought including quantum gravity, the process philosophers of the Axial Age, and the early modern process philosophers impacted by Darwin's theory of evolution, such as Bergson, Whitehead, and James. The remarkable alignment of these diverse perspectives from science and philosophy adds conviction and depth to the development of process complexity. We conclude by indicating how process complexity influences our approach to policy and management practice.

Complexity has received substantial attention from scientists and philosophers alike. There are numerous, often conflicting, accounts of how complexity should be defined and how it should be measured. Much less attention has been paid to the epistemic implications of complexity, especially in Ecology. How does the complex nature of ecological systems affect ecologists' ability to study them? This Element argues that ecological systems are complex in a rather special way: they are causally heterogeneous. Not only are they made up of many interacting parts, but their behaviour is variable across space or time. Causal heterogeneity is responsible for many of the epistemic difficulties that ecologists face, especially when making generalisations and predictions. Luckily, ecologists have the tools to overcome these difficulties, though these tools have historically been considered suspect by philosophers of science. The author presents an updated philosophical account with an optimistic outlook of the methods and status of ecological research.

Personal construct integrative complexity (I-C) refers to the assimilation of complex information into a system of impressions. Consistent with Kelly's (1955) theory of personal constructs, Chambers (1983; 1985) found I-C subjects tended to use a credulous approach to life and
were better at resolving conflicting information in forming impressions. In similar research, Crockett et al. (1975) showed a measure of cognitive complexity (C-C) interacted with a credulous cognitive set to be predictive of conflict resolution. In the present study, I-C and C-C are compared,
in interaction with cognitive set, as predictors of conflict resolution.