The digital revolution will make data abundant and cheap. Moving from a time of darkness into a digital age with information overload, we will need suitable filters. However, those who build these filters will determine what we see. This creates possibilities to influence people’s decisions such that they become remotely controlled rather than make their decisions on their own. Since omnibenevolent rule cannot be supposed and top-down control is flawed for several reasons, another approach is needed. It can be found with distributed control, collective intelligence and participation. “Nervousnet” will be presented as a feasible specimen of a Citizen Web.

 

From remote-controlled to self-controlled citizens

Helbing, D. Eur. Phys. J. Spec. Top. (2017). doi:10.1140/epjst/e2016-60372-1

Source: link.springer.com

Novelties are part of our daily lives. We constantly adopt new technologies, conceive new ideas, meet new people, experiment with new situations. Occasionally, we as individuals, in a complicated cognitive and sometimes fortuitous process, come up with something that is not only new to us, but to our entire society so that what is a personal novelty can turn into an innovation at a global level. Innovations occur throughout social, biological and technological systems and, though we perceive them as a very natural ingredient of our human experience, little is known about the processes determining their emergence. Still the statistical occurrence of innovations shows striking regularities that represent a starting point to get a deeper insight in the whole phenomenology. This paper represents a small step in that direction, focusing on reviewing the scientific attempts to effectively model the emergence of the new and its regularities, with an emphasis on more recent contributions: from the plain Simon’s model tracing back to the 1950s, to the newest model of Polya’s urn with triggering of one novelty by another. What seems to be key in the successful modelling schemes proposed so far is the idea of looking at evolution as a path in a complex space, physical, conceptual, biological, technological, whose structure and topology get continuously reshaped and expanded by the occurrence of the new. Mathematically it is very interesting to look at the consequences of the interplay between the “actual” and the “possible” and this is the aim of this short review.

 

Dynamics on expanding spaces: modeling the emergence of novelties
Vittorio Loreto, Vito D. P. Servedio, Steven H. Strogatz, Francesca Tria

Source: arxiv.org

Academic research is driven by several factors causing different disciplines to act as “sources” or “sinks” of knowledge. However, how the flow of authors’ research interests – a proxy of human knowledge – evolved across time is still poorly understood. Here, we build a comprehensive map of such flows across one century, revealing fundamental periods in the raise of interest in areas of human knowledge. We identify and quantify the most attractive topics over time, when a relatively significant number of researchers moved from their original area to another one, causing what we call a “diaspora of the knowledge” towards sinks of scientific interest, and we relate these points to crucial historical and political events. Noticeably, only a few areas – like Medicine, Physics or Chemistry – mainly act as sources of the diaspora, whereas areas like Material Science, Chemical Engineering, Neuroscience, Immunology and Microbiology or Environmental Science behave like sinks.

 

Quantifying the diaspora of knowledge in the last century
Manlio De Domenico, Elisa Omodei and Alex Arenas
Applied Network Science20161:15
DOI: 10.1007/s41109-016-0017-9

Source: appliednetsci.springeropen.com

Similar to the Autonomous Computing initiative, which has mainly been advancing techniques for self-optimization focusing on computing systems and infrastructures, Organic Computing (OC) has been driving the development of system design concepts and algorithms for self-adaptive systems at large. Examples of application domains include, for instance, traffic management and control, cloud services, communication protocols, and robotic systems. Such an OC system typically consists of a potentially large set of autonomous and self-managed entities, where each entity acts with a local decision horizon. By means of cooperation of the individual entities, the behavior of the entire ensemble system is derived. In this article, we present our work on how autonomous, adaptive robot ensembles can benefit from OC technology. Our elaborations are aligned with the different layers of an observer/controller framework, which provides the foundation for the individuals’ adaptivity at system design-level. Relying on an extended Learning Classifier System (XCS) in combination with adequate simulation techniques, this basic system design empowers robot individuals to improve their individual and collaborative performances, e.g., by means of adapting to changing goals and conditions. Not only for the sake of generalizability but also because of its enormous transformative potential, we stage our research in the domain of robot ensembles that are typically comprised of several quad-rotors and that organize themselves to fulfill spatial tasks such as maintenance of building facades or the collaborative search for mobile targets. Our elaborations detail the architectural concept, provide examples of individual self-optimization as well as of the optimization of collaborative efforts, and we show how the user can control the ensembles at multiple levels of abstraction. We conclude with a summary of our approach and an outlook on possible future steps.

 

An Organic Computing Approach to Self-Organizing Robot Ensembles

Sebastian von Mammen, Sven Tomforde and Jörg Hähner

Front. Robot. AI, 17 November 2016 | https://doi.org/10.3389/frobt.2016.00067

Source: journal.frontiersin.org