Complexity Digest

Špela Šalamon Andrew Ewing Greta Fox Stephane Bilodeau Carlos Gershenson Matti TJ Heino Yaneer Bar-Yam

WHN Science Communications 2024; 5 (1): 1-1.

The global impact of the COVID-19 pandemic persists, causing significant harm. Extensive evidence indicates that even mild infections and reinfections can result in symptomatic and subclinical health damage, disability, and persistent infection. Vascular impacts, neurotropism, and immune dysregulation lead to impaired organ function, increased morbidity and mortality, compromised work productivity, and a decline in overall health and quality of life. The uncontrolled spread of the virus is accelerating its evolution, outpacing the effectiveness of vaccines, treatments, and immune system adaptation. This preventable disease and others magnified by immune dysfunction are driving staff shortages, supply chain disruptions, and overwhelming healthcare systems. Despite the dire nature of the current conditions, knowledge and means are present to solve these problems. We present a science-based strategy for confronting the ongoing pandemic, including reducing airborne transmission through clean indoor air programs comparable with historical clean water programs. Public and professional education on the implications of repeated SARS-CoV-2 infections and utilizing known preventive measures can dramatically reduce transmission, which in turn reduces the rate of new variant introduction and strengthens the effectiveness of vaccines and treatments. It is essential to restore the prioritization of health and safety in healthcare and society.

Read the full article at: whn.global

Hiroki Sayama, Chrystopher L. Nehaniv

The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton’s self-reproducing loops which proved that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activities for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers’ attention back to how to make spatio-temporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions.

Read the full article at: arxiv.org

Maria Cristina Diamantini

Entropy 2023, 25(7), 984

In this review, we establish a relation between information erasure and continuous phase transitions. The order parameter, which characterizes these transitions, measures the order of the systems. It varies between 0, when the system is completely disordered, and 1, when the system is completely ordered. This ordering process can be seen as information erasure by resetting a certain number of bits to a standard value. The thermodynamic entropy in the partially ordered phase is given by the information-theoretic expression for the generalized Landauer bound in terms of error probability. We will demonstrate this for the Hopfield neural network model of associative memory, where the Landauer bound sets a lower limit for the work associated with ‘remembering’ rather than ‘forgetting’. Using the relation between the Landauer bound and continuous phase transition, we will be able to extend the bound to analog computing systems. In the case of the erasure of an analog variable, the entropy production per degree of freedom is given by the logarithm of the configurational volume measured in units of its minimal quantum.

Read the full article at: www.mdpi.com

Linghang Sun, Yifan Zhang, Cristian Axenie, Margherita Grossi, Anastasios Kouvelas, Michail A. Makridis

Major cities worldwide experience problems with the performance of their road transportation systems. The continuous increase in traffic demand presents a substantial challenge to the optimal operation of urban road networks and the efficiency of traffic control strategies. Although robust and resilient transportation systems have been extensively researched over the past decades, their performance under an ever-growing traffic demand can still be questionable. The operation of transportation systems is widely believed to display fragile property, i.e., the loss in performance increases exponentially with the linearly increasing magnitude of disruptions, which undermines their continuous operation. The risk engineering community is now embracing the novel concept of (anti-)fragility, which enables systems to learn from historical disruptions and exhibit improved performance as disruption levels reach unprecedented magnitudes. In this study, we demonstrate the fragile nature of road transportation systems when faced with either demand or supply disruptions. First, we conducted a rigorous mathematical analysis to theoretically establish the fragile nature of the systems. Subsequently, by taking into account real-world stochasticity, we implemented a numerical simulation with realistic network data to bridge the gap between the theoretical proof and the real-world operations, to study the impact of uncertainty on the fragile property of the systems. This work aims to help researchers better comprehend the necessity to explicitly consider antifragile design toward the application of future traffic control strategies, coping with constantly growing traffic demand and subsequent traffic accidents.

Read the full article at: arxiv.org

Binghamton Center of Complex Systems (CoCo) Seminar February 7, 2024 Pedro Márquez-Zacarías (Santa Fe Institute) 

Watch at: vimeo.com

Humans can live up to age 100, and not 1000 – why? Are there limits in how much our brains can think and compute? The laws of physics can help explain a lot, both about our own human bodies and how we are connected to life all around us.

Listen at: complexity.simplecast.com

Tomoko Sakiyama

Physica Scripta

Random Boolean Networks (RBNs) model complex networks with numerous variables, serving as a tool for gene expression and genetic regulation modeling. RBNs exhibit phase transitions, contingent on node degrees. Given the significance of phase transitions in collective behaviors, the study explores the relationship between RBNs and actual living system networks, which also display critical behaviors. Notably, living systems exhibit such behaviors even beyond the predicted critical point in RBNs. This paper introduces a novel RBNs model incorporating a rewiring process for edge connections/disconnections. In contrast to prior studies, our model includes artificial genes occasionally adding self-loops and creating an instant and temporal lookup table. Consequently, our proposed model demonstrates the edge of chaos at higher node degrees. It serves as an abstract RBNs model generating noisy behaviors from internal agent processes without external parameter tuning.

Read the full article at: iopscience.iop.org

The Complex Systems Society announces the ninth edition of the CSS Scientific Awards. 

The Emerging Researcher Award recognizes promising researchers in Complex Systems within 3 years of the PhD defense.

The Junior Scientific Award is aimed at recognizing excellent scientific record of young researchers within 10 years of the PhD defense.

The Senior Scientific Award will recognize outstanding contributions of Complex Systems scholars at whatever stage of their careers.

Deadline: April 30th, 2024.

See https://cssociety.org/community/awards for the list of previous awardees.

More at: cssociety.org

May 13-17, 2024 Villa del Grumello, Como, Italy

Over the past decade, computational social science (CSS) has risen as an interdisciplinary field that combines methods and theories from computer science, statistics, and social sciences to study complex social phenomena using computational tools and techniques. 

By leveraging the power of computing and data, computational social scientists aim to uncover patterns and trends in complex social systems that may be difficult or impossible to discern through traditional research methods. 

Topics of interest include social networks, online communities, opinion dynamics, and collective decision-making, among others. Computational social science has become increasingly important as our world becomes more digitised, and its insights have significant implications for fields such as public policy, marketing, and sociology.

The First edition of the school Computational Social Science: Advances, Challenges and Opportunities is designed to provide an intensive and immersive learning experience for graduate students, postdoctoral researchers, and early career faculty interested in utilising computational methods to study social phenomena. 

The school will be open to 45 selected students. Application deadline: February 25th, 2024

More at: css.lakecomoschool.org

20 years of CCS

Welcome to the 20th Conference on Complex Systems, CCS2024! The CCS is the flagship annual meeting for the complex systems research community, operating within the framework of the Complex Systems Society. This special 20th anniversary conference is jointly organised by Northeastern University London and the University of Exeter.

We welcome participants looking to appreciate the connection with the multidisciplinary community that CCS brings together. In this 20th edition of the conference we welcome young researchers for a warm-up session in beautiful London, followed by the main conference just a train ride away in Exeter.

More at: ccs24.cssociety.org

Len Fisher, Thilo Gross, Helmut Hillebrand, Anders Sandberg, Hiroki Sayama

People and NatureMany of the global challenges that confront humanity are interlinked in a dynamic complex network, with multiple feedback loops, nonlinear interactions and interdependencies that make it difficult, if not impossible, to consider individual threats in isolation.
These challenges are mainly dealt with, however, by considering individual threats in isolation (at least in political terms). The mitigation of dual climate and biodiversity threats, for example, is linked to a univariate 1.5°C global warming boundary and a global area conservation target of 30% by 2030.
The situation has been somewhat improved by efforts to account for interactions through multidimensional target setting, adaptive and open management and market-based decision pathways.
But the fundamental problem still remains—that complex systems such as those formed by the network of global threats have emergent properties that are more than the sum of their parts. We must learn how to deal with or live with these properties if we are to find effective ways to cope with the threats, individually and collectively.
Here, we argue that recent progresses in complex systems research and related fields have enhanced our ability to analyse and model such entwined systems to the extent that it offers the promise of a new approach to sustainability. We discuss how this may be achieved, both in theory and in practice, and how human cultural factors play an important but neglected role that could prove vital to achieving success.

Read the full article at: besjournals.onlinelibrary.wiley.com

Germans Savcisens, Tina Eliassi-Rad, Lars Kai Hansen, Laust Hvas Mortensen, Lau Lilleholt, Anna Rogers, Ingo Zettler & Sune Lehmann 
Nature Computational Science volume 4, pages 43–56 (2024

Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark across several years, and that includes information about life-events related to health, education, occupation, income, address and working hours, recorded with day-to-day resolution. We create embeddings of life-events in a single vector space, showing that this embedding space is robust and highly structured. Our models allow us to predict diverse outcomes ranging from early mortality to personality nuances, outperforming state-of-the-art models by a wide margin. Using methods for interpreting deep learning models, we probe the algorithm to understand the factors that enable our predictions. Our framework allows researchers to discover potential mechanisms that impact life outcomes as well as the associated possibilities for personalized interventions.

Read the full article at: www.nature.com

JUNWEI SU and PETER MARBACH

Advances in Complex Systems Vol. 26, No. 06, 2340004 (2023)

Empirical studies have consistently demonstrated the presence of a core–periphery structure within social network communities. Nevertheless, a formal model and comprehensive analysis to fully understand the structural characteristics of these communities are still lacking. This paper seeks to characterize these properties, focusing on agents’ interconnections and their allocation of rates. Employing a game-theoretic approach, our analysis unveils several novel insights. First, we show that periphery agents not only follow core agents but also other periphery agents who share similar primary interests. Second, our results illuminate the emergence of core–periphery communities, revealing the conditions under which they form, and how they form.

Read the full article at: www.worldscientific.com

Complexity72h is an interdisciplinary workshop designed for young researchers in complex systems, where participants collaborate in a project for 72 hours. Next edition will be held in Madrid from June 24th to 28th. These projects are led by experienced researchers who propose and guide them throughout the week. *The Call for Participants is currently open until February 29th*. To apply, you will need to provide some information about yourself, including your CV and a motivation letter. You will also need to read all the projects offered and rate each project, and to select a double (€320 fee) or single (€500 fee) room. The earlier you register, the higher the chance you will get the room you want. But do not worry: everybody will get accommodation!  Don’t worry if your CV is not fat. Complexity72h is looking for committed, hardworking and curious people! We aim at having participants coming from different stages of their careers: Master’s students, PhD students, and postdocs. We thus encourage Master and young PhD students to apply! We will award scholarships to motivated young students and researchers who may lack funding to attend Complexity72h. The number of scholarships and what they cover will depend on the funding we can secure. If you are interested in applying, you can do so in the application form. The fee includes: 

• The type of room selected
• Accommodation for 5 nights (check-in on Sunday, check-out on Friday)
• All meals (breakfast, lunch, dinner) starting on Monday at breakfast
• Nine coffee breaks
• The Madrid city tour on Sunday
• The social event/dinner on Monday evening
• Welcoming kit
• Several facilities for work, sport and leisure activities

 All relevant information can be found at https://complexity72h.com . If you are interested in participating, please don’t hesitate to apply, and spread the word among your fellow researchers!

JINLONG MA, TINGTING XIANG, and MINGWEI CAI

Advances in Complex Systems Vol. 26, No. 06, 2340005 (2023)

Multiplex networks have proven to be valuable tools for modeling and analyzing real complex system. Extensive work has been done on the traffic dynamics on multiplex networks, but there remains a lack of sufficient attention towards studying routing strategies for the purpose of suppressing epidemic spreading. In this paper, the impact of global awareness routing (GAR), improved global awareness routing (IGAR), and improved active routing (IAR) strategies on traffic-driven epidemic spreading are investigated. Our findings indicate that in the case of infinite node-delivery capacity and no traffic congestion in the network, adjusting routing parameters can effectively suppress epidemic spreading. In this context, these three strategies show better abilities on the multiplex network built by WS or ER model to minimize the density of infected nodes, thus contributing to the overall inhibition of the epidemic spread. However, in the multiplex network constructed by BA model, GAR strategy has a promoting effect on epidemic spreading compared with the shortest routing strategy. In addition, by controlling traffic flow, limiting node delivery capabilities can contain outbreaks. Our results suggest that adopting appropriate routing strategies in multiplex networks can play a proactive role in controlling epidemic spreading. This is crucial for formulating effective prevention and control measures and improving public health security.

Read the full article at: www.worldscientific.com

Lucila G. Alvarez-Zuzek, Jelena Grujic, Riccardo Gallotti

Sharing misinformation threatens societies as misleading news shapes the risk perception of individuals. We witnessed this during the COVID-19 pandemic, where misinformation undermined the effectiveness of stay-at-home orders, posing an additional obstacle in the fight against the virus. In this research, we study misinformation spreading, reanalyzing behavioral data on online sharing, and analyzing decision-making mechanisms using the Drift Diffusion Model (DDM). We find that subjects display an increased instinctive inclination towards sharing misleading news, but rational thinking significantly curbs this reaction, especially for more cautious and older individuals. Using an agent-based model, we expand this individual knowledge to a social network where individuals are exposed to misinformation through friends and share (or not) content with probabilities driven by DDM. The natural shape of the Twitter network provides a fertile ground for any news to rapidly become viral, yet we found that limiting users’ followers proves to be an appropriate and feasible containment strategy.

Read the full article at: arxiv.org

Federica De Domenico, Fabio Caccioli, Giacomo Livan, Guido Montagna, Oreste Nicrosini

Participants in socio-economic systems are often ranked based on their performance. Rankings conveniently reduce the complexity of such systems to ordered lists. Yet, it has been shown in many contexts that those who reach the top are not necessarily the most talented, as chance plays a role in shaping rankings. Nevertheless, the role played by chance in determining success, i.e., serendipity, is underestimated, and top performers are often imitated by others under the assumption that adopting their strategies will lead to equivalent results. We investigate the tradeoff between imitation and serendipity in an agent-based model. Agents in the model receive payoffs based on their actions and may switch to different actions by either imitating others or through random selection. When imitation prevails, most agents coordinate on a single action, leading to non-meritocratic outcomes, as a minority of them accumulates the majority of payoffs. Yet, such agents are not necessarily the most skilled ones. When serendipity dominates, instead, we observe more egalitarian outcomes. The two regimes are separated by a sharp transition, which we characterise analytically in a simplified setting. We discuss the implications of our findings in a variety of contexts, ranging from academic research to business.

Read the full article at: arxiv.org

TO BE HELD ONLINE ON MARCH 20-22, 2024

This FREE event brings together a wide range of speakers to discuss the many challenges and opportunities in Embodied Intelligence research! The workshop is structured with a morning session and afternoon session each day to accommodate different time zones. Each session includes plenary talks, panel discussions (including flash talks by leading researchers), and breakout sessions as shown in the tentative programme here. While plenary and panel speakers are invitation-only, we solicit wider contributions in breakout sessions to facilitate more focused and technical discussions.

Register at: embodied-intelligence.org

Bao Tran Truong, Oliver Melbourne Allen & Filippo Menczer
EPJ Data Science volume 13, Article number: 10 (2024)

The spread of misinformation poses a threat to the social media ecosystem. Effective countermeasures to mitigate this threat require that social media platforms be able to accurately detect low-credibility accounts even before the content they share can be classified as misinformation. Here we present methods to infer account credibility from information diffusion patterns, in particular leveraging two networks: the reshare network, capturing an account’s trust in other accounts, and the bipartite account-source network, capturing an account’s trust in media sources. We extend network centrality measures and graph embedding techniques, systematically comparing these algorithms on data from diverse contexts and social media platforms. We demonstrate that both kinds of trust networks provide useful signals for estimating account credibility. Some of the proposed methods yield high accuracy, providing promising solutions to promote the dissemination of reliable information in online communities. Two kinds of homophily emerge from our results: accounts tend to have similar credibility if they reshare each other’s content or share content from similar sources. Our methodology invites further investigation into the relationship between accounts and news sources to better characterize misinformation spreaders.

Read the full article at: epjdatascience.springeropen.com

María del Pilar García-Chitiva, Juan C. Correa

Is it possible to measure how critical soft skills like leadership or teamwork are from the viewpoint of graduate studies offerings? This paper provides a conceptual and methodological framework that introduces the concept of a bipartite network as a practical way to estimate the importance of soft skills as socio-emotional abilities trained in graduate studies. We examined 230 graduate programs offered by 49 higher education institutions in Colombia to estimate the empirical importance of soft skills from the viewpoint of graduate studies offerings. The results show that: a) graduate programs in Colombia share 31 soft skills in their intended learning outcomes; b) the centrality of these skills varies as a function of the graduate program, although this variation was not statistically significant; and c) while most central soft skills tend to be those related to creativity (i.e., creation or generation of ideas or projects), leadership (to lead or teamwork), and analytical orientation (e.g., evaluating situations and solving problems), less central were those related to empathy (i.e., understanding others and acknowledgment of others), ethical thinking, and critical thinking, posing the question if too much emphasis on most visible skills might imply an unbalance in the opportunities to enhancing other soft skills such as ethical thinking.

Read the full article at: arxiv.org