Complex systems Complex systems present problems both in mathematical modelling and philosophical foundations. The study of complex systems represents a new approach to science that investigates how relationships between parts give rise to the collective behaviors of a system and how the system interacts and forms relationships with its environment.[1] Such systems are used to model processes in computer science, biology,[2] economics, physics, chemistry,[3] and many other fields. The key problems of complex systems are difficulties with their formal modelling and simulation. For systems that are less usefully represented with equations various other kinds of narratives and methods for identifying, exploring, designing and interacting with complex systems are used. Overview[edit] History[edit] A history of complexity science Typical areas of study[edit] Complexity management[edit] Complexity economics[edit] Complexity and modeling[edit] Complexity and chaos theory[edit] 1. Institutes and research centers[edit]
Reportage Bhoutan : au pays du Bonheur National Brut De Marie-Monique Robin – ARTE GEIE / M2R Productions – France 2014 Niché au cœur de l’Himalaya, le petit royaume du Bhoutan a décidé d’en finir avec « la dictature du Produit Intérieur Brut (PIB) » et de la croissance économique à tout prix, en proposant un nouvel indicateur de richesse : le Bonheur National Brut (BNB). Lancé par le 4ème Roi, le « nouveau paradigme » s’appuie sur quatre piliers : la protection de l’environnement, la conservation et la promotion de la culture bhoutanaise, la bonne gouvernance et le développement économique responsable et durable. Œil pour Œil : les réfugiés de Calais De Lionel Charrier - Agence MYOP Une caméra regarde un appareil photo : l'idée est plutôt simple mais pourquoi faudrait-il se compliquer la tâche pour filmer au travail nos confrères photographes ? A Calais, de nombreux Syriens mènent une vie d'errance en attendant l'opportunité de passer en Angleterre.
Complexity There is no absolute definition of what complexity means, the only consensus among researchers is that there is no agreement about the specific definition of complexity. However, a characterization of what is complex is possible.[1] Complexity is generally used to characterize something with many parts where those parts interact with each other in multiple ways. The study of these complex linkages is the main goal of complex systems theory. In science,[2] there are at this time a number of approaches to characterizing complexity, many of which are reflected in this article. Overview[edit] Definitions of complexity often depend on the concept of a "system"—a set of parts or elements that have relationships among them differentiated from relationships with other elements outside the relational regime. Some definitions relate to the algorithmic basis for the expression of a complex phenomenon or model or mathematical expression, as later set out herein. Varied meanings of complexity[edit]
Systemtheorie Die Systemtheorie ist sowohl eine allgemeine und eigenständige Disziplin als auch ein weitverzweigter und heterogener Rahmen für einen interdisziplinären Diskurs, der den Begriff System als Grundkonzept führt. Es gibt folglich sowohl eine allgemeine „Systemtheorie“ als auch eine Vielzahl unterschiedlicher, zum Teil widersprüchlicher und konkurrierender Systemdefinitionen und -begriffe. Es hat sich heute jedoch eine relativ stabile Reihe an Begriffen und Theoremen herausgebildet, auf die sich der systemtheoretische Diskurs bezieht. Geschichte[Bearbeiten] Der Begriff Allgemeine Systemtheorie geht auf den Biologen Ludwig von Bertalanffy zurück. Kulturgeschichtlich geht der Systembegriff bis auf Johann Heinrich Lambert zurück und wurde unter anderem von Johann Gottfried Herder übernommen und ausgearbeitet. Die moderne Systemtheorie beruht auf unabhängig voneinander entwickelten Ansätzen, die später synthetisiert und erweitert wurden: Der Begriff Systemtheorie bzw. Kybernetik[Bearbeiten]
Mindfulness: more than a fad, less than a revolution. Meditation is simply about being yourself, and knowing something about who that is. - Jon Kabat-Zinn. (The following post is a selection of ideas and links to add some texture and critical apparatus to help people better engage with the growing mindfulness phenomenon. It is by no means an exhaustive account, and was written mostly to make sense of how mindfulness connects with RSA’s work, past and present, which I refer to at the end. While one can and should distinguish between mindfulness meditation and meditation in general, Kabat Zinn’s statement captures why RSA’s Social Brain centre is interested – mindfulness is a form of practice that helps to cultivate self-knowledge.) A colleague recently remarked that mindfulness was ‘on the way out’. And yet, people are right to react to the tendency to see mindfulness as a panacea before really knowing it deeply from a first, second or third person perspective. So when people say ‘mindfulness’ they can mean 1. Mindfulness in Parliament
Complexity theory and organizations Application of complexity theory to strategy Complexity theory and organizations, also called complexity strategy or complex adaptive organizations, is the use of the study of complexity systems in the field of strategic management and organizational studies.[1][2][3][4] It draws from research in the natural sciences that examines uncertainty and non-linearity.[5] Complexity theory emphasizes interactions and the accompanying feedback loops that constantly change systems. While it proposes that systems are unpredictable, they are also constrained by order-generating rules.[6]: 74 Complexity theory has been used in the fields of strategic management and organizational studies. Key concepts[edit] Complex adaptive systems[edit] Organizations can be treated as complex adaptive systems (CAS) as they exhibit fundamental CAS principles like self-organization, complexity, emergence,[9] interdependence, space of possibilities, co-evolution,[10] chaos,[11][12] and self-similarity.[7][13][14]
Complex adaptive system They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.[1][2] Overview[edit] The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. The fields of CAS and artificial life are closely related. The study of CAS focuses on complex, emergent and macroscopic properties of the system.[3][11][12] John H. General properties[edit] What distinguishes a CAS from a pure multi-agent system (MAS) is the focus on top-level properties and features like self-similarity, complexity, emergence and self-organization. Characteristics[edit] Some of the most important characteristics of complex systems are:[14] Robert Axelrod & Michael D.
La guerre pour l'argent Temps de lecture: 3 min Quand notre classe politique sortira de ses petites affaires et lèvera le nez au-delà des prochaines échéances électorales, elle découvrira que le monde qui vient est si lourd de menaces que les guerres sont à nouveau possibles. Telle est la sombre prédiction de Jean-Hervé Lorenzi, le président du Cercle des économistes, et de Mickaël Berrebi, auteurs d'un livre au titre glaçant: Un monde de violences. Les sources de conflits sont nombreuses et si «nous hésitons à évoquer la guerre… notre incapacité à les surmonter nous y conduira sans nul doute». On avait connu Lorenzi professeur d'optimisme, le voilà effrayant. Le livre est, hélas! On s'arrête sur la finance parce que l'ouvrage présente une thèse nette: le monde financier s'est autonomisé dans les dernières décennies et aucun retour en arrière n'est possible. Cette finance spéculative, inarrêtable, n'oeuvre plus que pour elle-même. Le livre ouvre d'autres pistes. Nous y revoilà, à notre classe politique.
Computational sociology Branch of the discipline of sociology Computational sociology is a branch of sociology that uses computationally intensive methods to analyze and model social phenomena. Using computer simulations, artificial intelligence, complex statistical methods, and analytic approaches like social network analysis, computational sociology develops and tests theories of complex social processes through bottom-up modeling of social interactions.[1] In relevant literature, computational sociology is often related to the study of social complexity.[5] Social complexity concepts such as complex systems, non-linear interconnection among macro and micro process, and emergence, have entered the vocabulary of computational sociology.[6] A practical and well-known example is the construction of a computational model in the form of an "artificial society", by which researchers can analyze the structure of a social system.[2][7] History[edit] Background[edit] Systems theory and structural functionalism[edit]
Cellular automaton The concept was originally discovered in the 1940s by Stanislaw Ulam and John von Neumann while they were contemporaries at Los Alamos National Laboratory. While studied by some throughout the 1950s and 1960s, it was not until the 1970s and Conway's Game of Life, a two-dimensional cellular automaton, that interest in the subject expanded beyond academia. In the 1980s, Stephen Wolfram engaged in a systematic study of one-dimensional cellular automata, or what he calls elementary cellular automata; his research assistant Matthew Cook showed that one of these rules is Turing-complete. Wolfram published A New Kind of Science in 2002, claiming that cellular automata have applications in many fields of science. The primary classifications of cellular automata as outlined by Wolfram are numbered one to four. Overview[edit] The red cells are the von Neumann neighborhood for the blue cell, while the extended neighborhood includes the pink cells as well. A torus, a toroidal shape History[edit]