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Singularity in Natural and Artificial Complex Systems (5 articles)

La notion de singularité est une notion étrange, typiquement « border-line », qui questionne la science, et notamment les sciences de la complexité, mais interroge aussi bien au-delà de cette sphère. Elle désigne en effet ce qui est particulier, original, unique, étonnant, ce qui se démarque nettement, et qui du coup peut être objet d’attention pour tout être de raison, du fait de l’étonnement et de la curiosité qu’elle suscite spontanément. Irréductibles par excellence, la singularité et le singulier ne semblent pouvoir être appréhendés que dans un cadre idiographique, voire descriptif, qui s’oppose au projet nomothétique et explicatif, schèmes dominants de tout projet scientifique moderne. Et de fait, la singularité, du fait de son unicité, échappe à l’expérience dans un premier temps, celle-ci nécessitant un minimum de répétitivité pour se construire. Et pourtant, la singularité est très certainement à l’origine de maintes découvertes, intervenues à partir de l’observation de faits qui semblaient singuliers, et sur lesquels des esprits curieux et logiques se sont penchés, à l’instar des princes de Sérendip, pour en inférer raisonnements, explications et concepts génériques. En ce sens, la singularité représente une nouveauté qui, lorsqu’elle est interprétée comme un élément signifiant, peut susciter un questionnement scientifique empirique et inductif. Mais la singularité renvoie aussi au curieux, au bizarre, à l’étrange, voire à l’inquiétante étrangeté, et finalement au monstrueux. Angoisse et fascination peuvent facilement être ressentis face à la singularité monstrueuse, ce qui peut être à la fois un frein puissant mais aussi une motivation haletante pour appréhender ces phénomènes, que leur origine soit contingente ou émergente. Ainsi, c’est en étudiant des objets mathématiques jugés « monstrueux » par les mathématiciens (il s’agissait d’objets complexes récursivement définis comme les éponges de Menger, la courbe ou le flocon de Von Koch, l’ensemble de Cantor, le tapis de Sierpinski, la courbe de Peano) que Mandelbrot a « inventé » les fractales. Ainsi la Teratologie, avec son cortège de monstres tour à tour grotesques, terrifiants, repoussants ou touchants, est un des horizons de la singularité, et nous interroge. Enfin la singularité est porteuse de différence, de positionnements en rupture, de nouveaux questionnements voire de subversion ou de folie. "La singularité est dangereuse en tout" disait Fénelon, car elle peut ouvrir des portes dont nul ne sait exactement où elles mènent. Il était totalement singulier pour Cristoforo Columbo de vouloir traverser une mer océanique qu’on pensait – en ignorant la science grecque-, plate et peuplée de démons, pour rejoindre par l’Ouest ce qui était à l’Est. C’est cette motivation qui a poussé Peter Diamandis et Ray Kurzweil (financés par la Nasa et Google) à fonder en 2009 « Singularity University », dans la Silicon Valley, dont l’objet est au fond de préparer les esprits au passage à la « transhumanité », c’est à dire à une humanité où esprits et technologies seront intimement liés dans une nouvelle symbiose qui bouleversera le monde et l’humanité telle que nous la connaissons. "Plus l'univers se standardise, plus la singularité m'intéresse" écrivait Claude Sautet, mobilisant la singularité en bouclier face à la prolétarisation qui touche nos sociétés modernes, et assujettit les personnes. En même temps, la Nasa et Google travaillent à partir du même concept à déconstruire l’homme biologique pour construire une nouvelle humanité, bio-technologique. Il y a donc bien quelque chose de vital et d’essentiel qui s’exprime à travers la singularité, mais aussi de terrifiant, lorsqu’on l’associe à la perspective de la transhumanité, ce qui fait du concept de singularité un concept fondamentalement dialogique. Nous sommes donc d’évidence devant une question fondamentale pour la science, mais aussi pour la société, voire l’humanité. La singularité méritait vraiment qu’on lui consacre une semaine à Rochebrune.


Graphs and social systems (6 articles)

A social system can be viewed as the set of relationships existing between entities such as individuals, groups, and institutions and forming a structured, coherent whole. Social system analysis is an inherently interdisciplinary academic field, which emerged from social psychology, sociology, statistics, graph theory, and other domains. For the last few decades, and in parallel with the development of the network science field, graph-based approaches dedicated to this purpose have gained a significant following in social sciences and humanities, and there are now tools commonly available for end-users. Thanks to the very generic nature of graphs, it is possible to take a method designed to handle a specific system, and apply it in a completely different context. For instance, a method allowing to detect functionally important proteins in a biological network can be used to identify key-players in a social network. However, due to lexical, methodological and cultural differences, being aware of the methods developed in other fields can be truly challenging for a researcher. The goal of this special issue is to try to bridge this gap, by exposing researchers to different tools and usages of the concept of graph, coming from out of their field. The general idea is to describe graph analysis methods and/or their application to specific social systems. We are interested in works proposing new analysis or extraction methods, likely to be used in various very different applicative contexts. We are also interested in works describing how an existing method, initially developed for a given context, was adapted and/or applied to graphs representing completely different systems. Finally, we are interested as well in works dealing with systems whose unique properties require the design of domain-specific methods.


Digital Contextualization (2 articles)

Sociologists like Pierre Bourdieu advocated the need of a relational type of analysis on data: Statistics, scores and answers to a questionnaire should be considered to relate individuals and highlight hidden complex factors.Data collected about individuals need to be contextualized relatively to other individuals, implicit social environment and culture at large. Correspondence Analysis based on Singular value decomposition (SVD) has been successful in contextualizing individual data to other individuals. Latent Semantic Analysis also based on SVD was successful in contextualizing words based on their usage context. These methods have been expanded in several directions. Partial Least Squares path modelling (PLS­pm) analysis allows the analysts to test hypotheses against data by integrating a simulation process. Latent Dirichlet Allocation has provided a probabilistic alternative to vector LSA. Along with these efficient numerical approaches, discrete approaches relying on the increasing computer power have explored non­frequentist approaches. These Formal Concept Analysis based on Galois Lattices allow highlighting and relate complex underlying concepts. More specifically, Information Visualisation based on graph algorithms like PathFinder and Social Network indicators have allowed domain and topic mapping from raw text. Further on, automatic summarization approaches combined with Information Retrieval approaches led to methods that can highlight the implicit context of a short message giving a large and reliable encyclopedic resource like the WikiPedia. Recently, Deep Learning based on Word Embedding approaches handle contextualization based on very large data sources. Pierre Bourdieu was limited by two obstacles: the power of computers that at the time did not allow him to explore all correlations and the cost of data digitization and the contextualization by correlation analysis could only be done at the initiative of the analyst and according to the choice made. However the digital world of the 21st century reversed this paradigm. Automatic contextualisation of our every action is sustained. Finally the removal of these two technical bottlenecks raises questions, data rights and other ethical issues. The special issue would include state of the art, automatic contextualization methods and would put into perspective representative case studies of these approaches. Each article would be reviewed by a multidisciplinary committee and will include thorough reviews by both sociologists and computer scientists or statisticians.


Asymmetry (3 articles)

Studies on complex systems have emerged during the recent decades. The origin, evolution, and expression of asymmetry became an essential part of numerous complex systems. The journal Nature stated in 2012, that, in modern sciences, asymmetry-related phenomena belong to the five challenges as hard as finding the Higgs boson and just as potentially transformative.1 Asymmetry-related phenomena are an integral part in new developments in arts, language, and social sciences. They become of increasing importance in economy and likewise in natural science such as mathematics, physics, and chemistry individually contribute along with biology to the advanced understanding of microscopic and macroscopic asymmetries. In the frame of the strongly interdisciplinary Asymmetry Project of UCA’s2 Academy of Excellence “Complex Systems”, we organized the First European Asymmetry Symposium (see http://feas.fr), 15–16 March 2018 in Nice, France. With more than 200 participants, 30 oral presentations, contributions of representatives at Cambridge University, Collège de France, and Max Planck Society, an orchestra with more than 50 musicians, and an artist exhibition from the National School of Fine Arts at the Villa Arson, the First European Asymmetry Symposium was highly successful. Scientific and public outreach of our Symposium were extraordinary as evidenced by illustrated reports published in Nature3,Le Monde4 and in Science & Vie. Based on the success of the Symposium and its scientific and public outreach, we now edit a Special Issue on Asymmetry of the journal JIMIS. Please submit your manuscript until the deadline June 30th, 2018. Complex asymmetric systems such as the origin and evolution of asymmetric life, asymmetric amplification, asymmetric structures, asymmetry in economy and art – to name a few – are far from being understood and expressed. We expect that fundamental questions can be answered only through a trans-disciplinary approach that systematically complements the knowledge acquired in the traditional individual disciplines. The Special Issue on Asymmetry will summarize recent advances in the field. This edition of the Special Issue on Asymmetry is accompanied by the foundation of a new European Asymmetry (EA) Institute5 based at UCA. The EA Institute will be a virtual institute without walls that organizes high-level asymmetry-related research and provides a trans-disciplinary infrastructure for academic exchanges via conferences, presentations, and summer schools.


Analysis of networks and graphs (6 articles)

Networks have become invaluable to model and simulate a number of real-world systems: social, biological, computer-related, or otherwise. Thanks to their generic nature, it is possible to take a method designed to handle a specific system, and apply it in a completely different context. For instance, a method allowing to detect functionally important proteins in a biological network can be used to identify key-players in a social network. However, due to lexical, methodological and cultural differences, being aware of methods developed in other fields can be truly challenging for a researcher. The goal of this special issue is to try to bridge this gap between scientific fields, by exposing researchers to different tools and usages of the concept of graph, coming from out of their field. The general idea is to describe graph analysis methods and/or their application to specific social systems. We are interested in works proposing new analysis or extraction methods, likely to be used in various very different application contexts. We are also interested in works describing how an existing method, initially developed for a given context, was adapted and/or applied to graphs representing completely different systems. Finally, we are interested as well in works dealing with systems whose unique properties require the design of domain-specific methods.