Networking the complexity community since 1999
Author: cxdig
The recent availability of massive amounts of digital data have profoundly revolutionized research on migration and mobility, enabling scientists to quantitatively study individual and collective mobility patterns at different granularities as generated by human activities in their daily life.
Read the full article at: www.demogr.mpg.de
”Guided Self-Organization: Machine Learning in Embodied Agents”
The 11th International Conference on Guided Self-Organization takes place during 12-14 February 2025 in Tübingen, Germany. GSO-2025 is organized by The University of Tübingen, The Hamburg University of Technology, The Max Planck Institute for Intelligent Systems, and The International Association for Guided Self-Organization (TIA-GSO).
Research Aims and Topics
The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization (simplicity, parallelization, adaptability, robustness, scalability) while still being able to direct the outcome of the self-organizing process. GSO typically has the following features: (i) an increase in organization (structure and/or functionality) over some time; (ii) the local interactions are not explicitly guided by any external agent; (iii) task-independent objectives are combined with task-dependent constraints.
GSO “aims to regulate self-organization for specific purposes, so that a dynamical system may reach specific attractors or outcomes. The regulation constrains a self-organizing process within a complex system by restricting local interactions between the system components, rather than following an explicit control mechanism or a global design blueprint.” Information theory, nonlinear dynamics and network theory are core to many of these methods, and quantifying complexity, its sources and effects is a common theme.
The GSO-2025 conference will bring together invited experts and researchers in machine learning, artificial life, self-organizing systems, and complex adaptive systems, with particular emphasis on autonomous agents, information theory, critical phenomena and emergent behaviour. Special topics of interest include: reinforcement learning, intrinsic motivations, origin of life, systems biology, physics of life, unconventional computation, swarm intelligence, measures of complexity, criticality, complex networks, information-driven self-organization (IDSO), etc.
The program includes three days, with five keynote talks, and a number of regular onsite presentations on each day. There are no registration fees for the conference.
More at: www.guided-self.org
Please join us to celebrate 20 years of the Places & Spaces: Mapping Science exhibit! The exhibit is curated here at CNS and has traveled the globe showcasing best examples of information visualization.
When? June 6, 2024 from 4PM to 6PM EDT.
Where? In person at University Collections at McCalla, 525 E 9th St., Bloomington, IN 47408 or online via Zoom webinar.
What? Reception. Enjoy refreshments, remarks from the exhibition curators, presentations from teams whose works have been selected for inclusion in the exhibit this year, and the opportunity to try out a data visualization in VR.
Why? To introduce the latest additions to the exhibit and celebrate the 20th anniversary of the inception of the Places & Spaces: Mapping Science exhibit, see 100 maps and 40 interactive macroscopes at scimaps.org.
More at: cns-iu.github.io
Andrea Musso and Dirk Helbing
Royal Society Open Science
May 2024 Volume 11Issue 5
Socio-diversity, the variety of human opinions, ideas, behaviours and styles, has profound implications for social systems. While it fuels innovation, productivity and collective intelligence, it can also complicate communication and erode trust. So what mechanisms can influence it? This paper studies how fundamental characteristics of social networks can support or hinder socio-diversity. It employs models of cultural evolution, mathematical analysis and numerical simulations. We find that pronounced inequalities in the distribution of connections obstruct socio-diversity. By contrast, the prevalence of close-knit communities, a scarcity of long-range connections, and a significant tie density tend to promote it. These results open new perspectives for understanding how to change social networks to sustain more socio-diversity and, thereby, societal innovation, collective intelligence and productivity.
Read the full article at: royalsocietypublishing.org
Rafael Prieto-Curiel, Ola Ali, Elma Dervić, Fariba Karimi, Elisa Omodei, Rainer Stütz, Georg Heiler, Yurij Holovatch
PNAS Nexus, Volume 3, Issue 5, May 2024, page 178,
Migration’s impact spans various social dimensions, including demography, sustainability, politics, economy, and gender disparities. Yet, the decision-making process behind migrants choosing their destination remains elusive. Existing models primarily rely on population size and travel distance to explain the spatial patterns of migration flows, overlooking significant population heterogeneities. Paradoxically, migrants often travel long distances and to smaller destinations if their diaspora is present in those locations. To address this gap, we propose the diaspora model of migration, incorporating intensity (the number of people moving to a country), and assortativity (the destination within the country). Our model considers only the existing diaspora sizes in the destination country, influencing the probability of migrants selecting a specific residence. Despite its simplicity, our model accurately reproduces the observed stable flow and distribution of migration in Austria (postal code level) and US metropolitan areas, yielding precise estimates of migrant inflow at various geographic scales. Given the increase in international migrations, this study enlightens our understanding of migration flow heterogeneities, helping design more inclusive, integrated cities.
Read the full article at: academic.oup.com
