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Related:  Complex SystemsThéorie & réflexions autour de l'IC

The human microbiome: Me, myself, us WHAT’S a man? Or, indeed, a woman? Biologically, the answer might seem obvious. A healthy adult human harbours some 100 trillion bacteria in his gut alone. And it really is a system, for evolution has aligned the interests of host and bugs. That bacteria can cause disease is no revelation. A bug’s life One way to think of the microbiome is as an additional human organ, albeit a rather peculiar one. The microbiome, too, is organised. Specialised; but not monotonous. That detail is significant. This early nutritional role, moreover, is magnified throughout life. The fat of the land This role in nutrition points to one way in which an off-kilter microbiome can affect its host: what feeds a body can also overfeed or underfeed it. Experiments on mice suggest this is not just a question of the bacteria responding to altered circumstances. Having shown that gut bacteria are involved in obesity, Dr Gordon wondered if the converse was true. The diabetes in question is known as type-2.

Pour une critique de l’intelligence collective Texte initialement publié en avril 1996 L'intelligibilité va avec l'immatérialité. Thomas d'Aquin Il faut se rendre à l'évidence: nous vivons un véritable Cyber-Bang, aux conséquences imprévisibles. L'économie du virtuel commence à façonner en profondeur une nouvelle société, en accélérant la dématérialisation des flux, en augmentant les court-circuits informationnels, en restucturant les marchés du traitement de l'information, en généralisant la "désintermédiation", mais aussi en provoquant de nouvelles inégalités culturelles entre "info-riches" et "info-pauvres". A. 1. "Un mot est encore l'homme, deux mots sont déjà l'abîme" - dit Roberto Juarroz. Il y a cependant une différence radicale entre le langage naturel et la formalisation mathématique: les mathématiques favorisent l'induction et la généralisation. Il y a la raison qui se porte sur les essences en tant qu'elles sont connues, clarifiées, et la raison qui se porte sur les essences en tant qu'elles sont cachées, obscures. 2. 3. 4.

The home of stigmergic systems Think Complexity by Allen B. Downey Buy this book from Download this book in PDF. Read this book online. Description This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. Free books! This book is under the Creative Commons Attribution-NonCommercial 3.0 Unported License, which means that you are free to copy, distribute, and modify it, as long as you attribute the work and don't use it for commercial purposes. Download the LaTeX source code (with figures and a Makefile) in a zip file.

Conduite du changement et utilisation de la courbe du deuil : PRUDENCE ! « EOMA Dans l’apprentissage des méthodes en conduite du changement, l’un des premiers points abordés est la "résistance" au changement. Pour illustrer ce processus de "résistance", puis celui de son acceptation, on utilise un schéma, une courbe nommée la "vallée de la peur" ou la" vallée des larmes". Il faut être extrêmement prudent quant à l’usage de cet "outil". En effet, cette courbe représente avant tout les phases du processus de deuil décrites par la psychiatre et psychologue américaine Elisabeth Kübler-Ross, qui a consacré son travail à l’accompagnement des personnes en soins palliatifs et à l’accompagnement de leurs proches. L’annonce de la mort proche provoque les réactions suivantes : Mais au sein de l’entreprise, avant de plaquer ce schéma sur les réactions présumées des collaborateurs à l’annonce d’un nouveau projet et des changements qu’il induit, il faut rappeler que le processus de deuil est un processus individuel et personnel. Clotilde Nicol Like this: J'aime chargement…

Biological system design From the CD-ROM "Concepts and strategies" by Peter Small Modular route to complexity The ideas for creating stigmergic systems for the Web originated during the writing of the two books Lingo Sorcery and Magical A-Life Avatars (written for multimedia designers who wanted to learn how to use lists and objects). The central theme of these books was to show how object oriented programming techniques can be used to develop products that went beyond a developer's imagination. It was found that designing systems in this way, resulted in productions that went not only beyond the designer's imagination, but also beyond the designer's ability to comprehend the growing complexity that begins to emerge. It soon became clear that we were dealing with something far more exciting than mere computer programming; we were entering the esoteric world of chaos and complexity theory. Amazingly, this did not lead to the design of large, complicated programs. Objects Understanding objects Creating a new generation

Intelligent Complex Adaptive Systems I don’t believe in the existence of a complex systems theory as such and, so far, I’m still referring to complex systems science (CSS) in order to describe my research endeavours. In my view, the latter is constituted, up until now, by a bundle of loosely connected methods and theories aiming to observe— from contrasted standpoints—these fascinating objects of research called complex adaptive systems. Nearly 40 years after Von Bertalanffy’s General System Theory (1968) and Jacques Monod’s Chance and Necessity (1971), it is fair to look back and to try to assess how much remains to be said about these complex adaptive systems. After all, Prigogine’s Order out of Chaos (1984) already demonstrated that future wasn’t entirely predictable in a history- contingent world. The universe is a massive system of systems -- for example, ecological systems, social systems, commodity and stock markets.

Gérer le changement à chaque phase traversée par les acteurs d’un projet Face au changement qu’entraîne le déploiement d’un nouvel outil informatique, l’individu est amené à traverser quatre étapes de transition. Selon l’individu, la durée de ces quatre phases sera plus ou moins importante et évoluera en fonction de facteurs internes et/ou externes au projet. Ainsi, afin d’adapter son message et sa stratégie de conduite du changement, le consultant en Système d’Information doit être capable de déterminer avec précision la phase par laquelle passe chacun des acteurs. Cela permet également de mettre en place un changement de manière continue et progressive tout en prenant en compte les différences de ressenti de chacun. L’étape de choc et de déni Elle entraîne un refus de voir et de prendre en compte l’arrivée du nouveau système d’information. Quelques craintes fréquentes : « Si l’informatique fait tout à ma place, je risque de perdre mon emploi » ou « Mes habitudes de travail vont être modifiées du jour au lendemain ! L’étape de révolte La phase d’exploration

Acta Astronautica - Stigmergy based behavioural coordination for satellite clusters Abstract Multi-platform swarm/cluster missions are an attractive prospect for improved science return as they provide a natural capability for temporal, spatial and signal separation with further engineering and economic advantages. As spacecraft numbers increase and/or the round-trip communications delay from Earth lengthens, the traditional “remote-control” approach begins to break down. An autonomous group of spacecraft requires coordination, but standard terrestrial paradigms such as negotiation, require high levels of inter-spacecraft communication, which is nontrivial in space. After outlining the system, an analysis of some crucial parameters such as communications overhead and number of spacecraft is presented to demonstrate scalability. Keywords Stigmergy; Satellite cluster; Autonomy; Distributed; Coordination; Task allocation Copyright © 2009 Elsevier Ltd.

Complex systems made simple Albert-László Barabási and Yang-Yu Liu, together with their collaborator Jean-Jacques Slotine at M.I.T., have developed a method for observing large, complex systems. In the image above, red dots represent sensor nodes, which are required to reconstruct the entire internal state of one such system. Image by Mauro Martino. Just as the name implies, com­plex sys­tems are dif­fi­cult to tease apart. But that may not matter any­more. The approach takes advan­tage of the inter­de­pen­dent nature of com­plexity to devise a method for observing sys­tems that are oth­er­wise beyond quan­ti­ta­tive scrutiny. “Con­nect­ed­ness is the essence of com­plex sys­tems,” said Albert-​​László Barabási, one of the paper’s authors and a Dis­tin­guished Pro­fessor of Physics with joint appoint­ments in biology and the Col­lege of Com­puter and Infor­ma­tion Sci­ence. Using their novel approach, the researchers first iden­tify all the math­e­mat­ical equa­tions that describe the system’s dynamics.

Authentic Community Leadership Stigmergic Cognition All things stigmergy Special Issue of Cognitive Systems Research Join the Linkedin Stigmergy group: Agents interact with others and their environment to circumvent cognitive limitation. Stigmergy is a property supervening on informational amplification and decay in complex adaptive social environments, environments that have sets of “search space” constraints. Though the concept of stigmergy has been associated with ant- or swarm-like “agents” with minimal cognitive ability, stigmergy offers a powerful analytical tool to be deployed in the human domain. • A context or environment: o Comprised by an indefinite number of local environments o Only partially perceivable through an internal dynamics that govern its temporal evolution • Agents: o There are a multiplicity of agents populating with no one individual or clustering of individuals having global knowledge o Rationality is bounded o Behavior is self-organized o Behavior is stochastic o Behavior is dynamical Like this: Like Loading...

Observability of complex systems Author Affiliations Edited by Giorgio Parisi, University of Rome, Rome, Italy, and approved December 26, 2012 (received for review September 6, 2012) Abstract A quantitative description of a complex system is inherently limited by our ability to estimate the system’s internal state from experimentally accessible outputs. Footnotes Author contributions: Y.

L'exemple le plus abouti d'intelligence collective... by noosquest Sep 1