Complexity Digest

García-Rodríguez A, Govezensky T, Naumis GG, Barrio RA

PLoS ONE 19(2): e0298791

Although friendship networks have been extensively studied, few models and studies are available to understand the reciprocity of friendship and foes. Here a model is presented to explain the directed friendship and foes network formation observed in experiments of Mexican and Hungarian schools. Within the presented model, each agent has a private opinion and a public one that shares to the group. There are two kinds of interactions between agents. The first kind represent interactions with the neighbors while the other represents the attitude of an agent to the overall public available information. Links between agents evolve as a combination of the public and private information available. Friendship is defined using a fitness function according to the strength of the agent’s bonds, clustering coefficient, betweenness centrality and degree. Enmity is defined as very negative links. The model allows us to reproduce the distribution of mentions for friends and foes observed in the experiments, as well as the topology of the directed networks.

Read the full article at: journals.plos.org

Tazzio Tissot, Mike Levin, View Chris Buckley, Richard Watson

How do multiple active components at one level of organisation create agential wholes at higher levels of organisation? For example, in organismic development, how does the multi-scale autonomy of the organism arise from the interactions of the molecules, cells and tissues that an organism contains? And, in the major evolutionary transitions, how does a multicellular organism, for example, arise as an evolutionary unit from the selective interests of its unicellular ancestors? We utilise computational models as a way to think about this general question. We take a deliberately minimalistic notion of an agent: a competency to take one of two possible actions to minimise stress. Helping ourselves to this behaviour at the microscale, we focus on conditions where this same type of agency appears spontaneously at a higher level of organisation. We find that a simple process of positive feedback on the timing of individual responses, loosely analogous to the natural phase synchronisation of weakly coupled oscillators, causes such a transition in behaviour. The emergent collectives that arise become, quite suddenly, able to respond to their external stresses in the same (minimal) sense as the original microscale units. This effects a dramatic rescaling of the system behaviour, and a quantifiable increase in problem-solving competency, serving as a model of how higher-level agency emerges from a pool of lower-level agents or active matter. We discuss how this dynamical ‘waking-up’ of higher-level collectives, through the alignment of their internal dynamics, might relate to reproductive/cell-cycle synchronisation in evolutionary transitions and development.

Read the full article at: www.biorxiv.org

Babak M. S. Arani, Stephen R. Carpenter, Egbert H. van Nes, Ingrid A. van de Leemput, Chi Xu, Pedro G. Lind, Marten Scheffer

Tipping points and alternative attractors have become an important focus of research and public discussions about the future of climate, ecosystems and societies. However, empirical evidence for the existence of alternative attractors remains scarce. For example, bimodal frequency distributions of state variables may suggest bistability, but can also be due to bimodality in external conditions. Here, we bring a new dimension to the classical arguments on alternative stable states and their resilience showing that the stochastic regime can distort the relationship between the probability distribution of states and the underlying attractors. Simple additive Gaussian white noise produces a one-to-one correspondence between the modes of frequency distributions and alternative stable states. However, for more realistic types of noise, the number and position of modes of the frequency distribution do not necessarily match the equilibria of the underlying deterministic system. We show that data must represent the stochastic regime as thoroughly as possible. When data are adequate then existing methods can be used to determine the nature of the underlying deterministic system and noise simultaneously. This may help resolve the question of whether there are tipping points, but also how realized states of a system are shaped by stochastic forcing vs internal stability properties.

Read the full article at: www.biorxiv.org

After the success of previous editions, we are pleased to announce the 5th Edition of the World Conference on Complex Systems, WCCS24. This conference will be organized by the “Faculty of Science and Technology of Mohammadia (FSTM), affiliated with Hassan II University of Casablanca”, in partnership with the “ Moroccan Society of Interdisciplinary Sciences” . WCCS24 will take place from November 11 to 14, 2024, in Casablanca, Morocco

WCCS24 will provide an international forum for researchers and Ph.D. students to present recent research results, address new challenges, and discuss emerging trends in the field of complex systems and interdisciplinary science.

The conference aims to foster a debate on the most relevant methodologies and approaches for understanding, modeling, simulating, predicting, evaluating, and mastering societal, ecological, biological, and engineered complex systems..

More at: mscomplexsystems.org

Daniel Hoyer, Samantha Holder, James S Bennett, Pieter François, Harvey Whitehouse, Alan Covey, Gary Feinman, Andrey Korotayev, Vadim Vustiuzhanin, Johannes Preiser-Kapeller, Kathryn Bard, Jill Levine, Jenny Reddish, Georg Orlandi, Rachel Ainsworth, and Peter Turchin

Societal ‘crises’ are periods of turmoil and destabilization in socio-cultural, political, economic, and other systems, often accompanied by varying amounts of violence and sometimes significant changes in social structure. The extensive literature analyzing societal crises has concentrated on relatively few historical examples (large-scale events such the fall of the Roman Empire or the French and Russian Revolutions) emphasizing different aspects of these events as potential causes or consistent effects. To investigate crises and prior approaches to explaining them, and to avoid a potential small-sample size bias present in several previous studies, we sought to uniformly characterize a substantial collection of historical crises, spanning millennia, from the prehistoric to post-industrial, and afflicting a wide range of polities in diverse global regions; the Crisis Database (CrisisDB). Here, we describe this dataset which comprises 168 crises suggested by historians and characterized by a number of significant ‘consequences’ (such as civil war, epidemics, or loss of population) including also institutional and cultural reforms (for example improved sufferance or constitutional changes) that might occur during and immediately following the crisis period. Our analyses show that the consequences experienced by each crisis is highly variable. The outcomes themselves are uncorrelated with one another and, overall, the set of consequences is largely unpredictable when compared to other large-scale properties of society suggested by previous scholars such as its territorial size, religion, administrative size, or historical recency. We conclude that there is no ‘typical’ societal crisis of the past, but crisis situations can take a variety of different directions. We offer some suggestions on the forces that might drive these varying consequences for exploration in future work.

Read the full article at: osf.io

Fernando E. Rosas, Bernhard C. Geiger, Andrea I Luppi, Anil K. Seth, Daniel Polani, Michael Gastpar, Pedro A.M. Mediano

Understanding the functional architecture of complex systems is crucial to illuminate their inner workings and enable effective methods for their prediction and control. Recent advances have introduced tools to characterise emergent macroscopic levels; however, while these approaches are successful in identifying when emergence takes place, they are limited in the extent they can determine how it does. Here we address this limitation by developing a computational approach to emergence, which characterises macroscopic processes in terms of their computational capabilities. Concretely, we articulate a view on emergence based on how software works, which is rooted on a mathematical formalism that articulates how macroscopic processes can express self-contained informational, interventional, and computational properties. This framework establishes a hierarchy of nested self-contained processes that determines what computations take place at what level, which in turn delineates the functional architecture of a complex system. This approach is illustrated on paradigmatic models from the statistical physics and computational neuroscience literature, which are shown to exhibit macroscopic processes that are akin to software in human-engineered systems. Overall, this framework enables a deeper understanding of the multi-level structure of complex systems, revealing specific ways in which they can be efficiently simulated, predicted, and controlled.

Read the full article at: arxiv.org

R Alexander Bentley, Benjamin Horne, Joshua Borycz, Simon Carrignon, Garriy Shteynberg, Blai Vidiella, Sergi Valverde, and Michael J O’Brien

Adaptive Behavior Volume 32, Issue 2

Diversity of expertise is inherent to cultural evolution. When it is transparent, diversity of human knowledge is useful; when social conformity overcomes that transparency, “expertise” can lead to divisiveness. This is especially true today, where social media has increasingly allowed misinformation to spread by prioritizing what is recent and popular, regardless of validity or general benefit. Whereas in traditional societies there was diversity of expertise, contemporary social media facilitates homophily, which isolates true subject experts from each other and from the wider population. Diversity of knowledge thus becomes social division. Here, we discuss the potential of a cultural-evolutionary framework designed for the countless choices in contemporary media. Cultural-evolutionary theory identifies key factors that determine whether communication networks unify or fragment knowledge. Our approach highlights two parameters: transparency of information and social conformity. By identifying online spaces exhibiting aggregate patterns of high popularity bias and low transparency of information, we can help define the “safe limits” of social conformity and information overload in digital communications.

Read the full article at: journals.sagepub.com

Victor Maull , Jordi Pla Mauri , Nuria Conde Pueyo and Ricard Solé

JRS Interface February 2024 Volume 21 Issue 211

The idea that the Earth system self-regulates in a habitable state was proposed in the 1970s by James Lovelock, who conjectured that life plays a self-regulatory role on a planetary-level scale. A formal approach to such hypothesis was presented afterwards under a toy model known as the Daisyworld. The model showed how such life-geosphere homeostasis was an emergent property of the system, where two species with different properties adjusted their populations to the changing external environment. So far, this ideal world exists only as a mathematical or computational construct, but it would be desirable to have a real, biological implementation of Lovelock’s picture beyond our one biosphere. Inspired by the exploration of synthetic ecosystems using genetic engineering and recent cell factory designs, here we propose a possible implementation for a microbial Daisyworld. This includes: (i) an explicit proposal for an engineered design of a two-strain consortia, using pH as the external, abiotic control parameter and (ii) several theoretical and computational case studies including two, three and multiple species assemblies. The special alternative implementations and their implications in other synthetic biology scenarios, including ecosystem engineering, are outlined.

Read the full article at: royalsocietypublishing.org

Lucas Böttcher and Mason A. Porter

Phys. Rev. E 109, 024314

In many studies, it is common to use binary (i.e., unweighted) edges to examine networks of entities that are either adjacent or not adjacent. Researchers have generalized such binary networks to incorporate edge weights, which allow one to encode node–node interactions with heterogeneous intensities or frequencies (e.g., in transportation networks, supply chains, and social networks). Most such studies have considered real-valued weights, despite the fact that networks with complex weights arise in fields as diverse as quantum information, quantum chemistry, electrodynamics, rheology, and machine learning. Many of the standard network-science approaches in the study of classical systems rely on the real-valued nature of edge weights, so it is necessary to generalize them if one seeks to use them to analyze networks with complex edge weights. In this paper, we examine how standard network-analysis methods fail to capture structural features of networks with complex edge weights. We then generalize several network measures to the complex domain and show that random-walk centralities provide a useful approach to examine node importances in networks with complex weights.

Read the full article at: link.aps.org

Tiny clumps of cells show basic cognitive abilities, and some animals can remember things after losing their head

Read the full article at: www.scientificamerican.com

Welcome to the first episode of the What ALife! Podcast! In this episode, I speak with Hiroki Sayama – Professor in the Department of Systems Science and Industrial Engineering, and the Director of the Binghamton Center of Complex Systems (CoCo), at Binghamton University (USA) – about all things cellular automata (CA): what they are, where they came from, what they are useful for; as well as his own ground-breaking work in CA systems in the late 90s. We also talk about continuous CA, and what the future of CA might look like.
We also discuss his more recent work modelling the spread of covid-19 and how artificial life researchers can help address complex societal problems, based on a ⁠short paper of the same name (direct.mit.edu/isal/proceedings/…2021/33/21/102961)

Listen at: soundcloud.com

Binghamton Center of Complex Systems (CoCo) Seminar
January 24, 2024
Sadamori Kojaku (Systems Science and Industrial Engineering, Binghamton University)
“Unsupervised Embedding of Trajectories Captures the Latent Structure of Scientific Migration”

Watch at: vimeo.com

Thomas F. Varley, Olaf Sporns, Nathan J. Stevenson, Martha G. Welch, Michael M. Myers, Sampsa Vanhatalo, Anton Tokariev

The human brain is a complex organ comprising billions of interconnected neurons which enables interaction with both physical and social environments. Neural dynamics of the whole brain go far beyond just the sum of its individual elements; a property known as “synergy”. Previously it has been shown that synergy is crucial for many complex brain functions and cognition, however, it remains unknown how and when the large number of discrete neurons evolve into the unified system able to support synergistic interactions. Here we analysed high-density electroencephalography data from late fetal to early postnatal period. We found that the human brain transitions from redundancy-dominated to synergy-dominated system around birth. Frontal regions lead the emergence of a synergistic scaffold comprised of overlapping subsystems, while the integration of sensory areas developed gradually, from occipital to central regions. Strikingly, early developmental trajectories of brain synergy were modulated by environmental enrichment associated with enhanced mother-infant interactions, and the level of synergy near term equivalent age was associated with later neurocognitive development

Read the full article at: www.biorxiv.org

The recent COVID-19 pandemic has demonstrated the power of modeling to support policymaking. However, most South American countries lack capacity in the field of modeling. This seven-day school will address how modeling allows us to use the health resources we currently have more efficiently, increasing their impact, improving people’s well-being, and saving lives as a result. The school includes a course on epidemic models, on numerical treatment of models and on epidemiological data analysis, and will be focused on group work involving “hands-on” modeling challenges. There will be classes in the morning and group projects in the afternoon. Participants from all areas related to the subject are welcome to apply. Knowledge of basic differential calculus is required.

Apply at: www.ictp-saifr.org

Chris Fields, James F. Glazebrook, and Michael Levin

Entropy 2024, 26(3), 194

The ideas of self-observation and self-representation, and the concomitant idea of self-control, pervade both the cognitive and life sciences, arising in domains as diverse as immunology and robotics. Here, we ask in a very general way whether, and to what extent, these ideas make sense. Using a generic model of physical interactions, we prove a theorem and several corollaries that severely restrict applicable notions of self-observation, self-representation, and self-control. We show, in particular, that adding observational, representational, or control capabilities to a meta-level component of a system cannot, even in principle, lead to a complete meta-level representation of the system as a whole. We conclude that self-representation can at best be heuristic, and that self models cannot, in general, be empirically tested by the systems that implement them.

Read the full article at: www.mdpi.com

Application for the second Complexity Global School – to be hosted simultaneously at Universidad de los Andes, Colombia, and Santa Fe Institute, USA from July 21 to August 3 – is now open. Applicants based in Latin America and the Caribbean are eligible for the Colombia location, and applicants based in USA, Canada, and western Europe are eligible for the USA location. Supported by the Omidyar Network, the school is free for all admitted students, inclusive of tuition, room, board, and travel stipend.

Read the full article at: www.santafe.edu

To extend the reach and diversity of its annual meetings, the American Physical Society has developed a pilot program of APS Satellite Meetings with the participation of ICTP-SAIFR in Latin America. As part of the APS March Meeting from March 3-8, 2024, ICTP-SAIFR is organizing on March 5 (Tuesday) a 2-hour Satellite Session on Complex Systems that will be broadcast live to all participants of the APS March Meeting, as well as a session on Complex Systems for student/postdoc presentations.

Graduate students and postdocs can apply until February 10, 2024 to give oral presentations or posters at the student-postdoc session on complex systems.

More at: www.ictp-saifr.org

F. Al Reda, S. Faure, B. Maury, E. Pinsard

Journal of Computational Physics

• Numerical investigation of the Faster is Slower effect based on a parameter free model.

• Integration of an inhibition tendency of polite pedestrians.

• Numerical evidence of the fluidizing role of an obstacle upstream the exit during evacuation.

• Numerical recovering of an experimental power law for time lapses.

Read the full article at: www.sciencedirect.com

The Complex Systems Society (CSS) organizes every year a main conference (CCS) – the most important annual meeting for the complex systems research community.

The Complex Systems Society invites bids to host the edition for 2025.

The conference is generally held in September/October of each year.

Interested potential organizers should send a short document (6 pages max.) detailing the proposal to the Society account css@cssociety.org (please add jfmendes@ua.pt and jramasco@ifisc.uib-csic.es in cc).

The last edition was in Salvador, Brasil (CCS2023). The next one will be in Exeter/London, UK (CCS2024).

The CCS series in recent years alternates between Europe, Asia and the Americas. In the edition 2025, preference will be given to bids from outside Europe in this edition even though bids from other locations will be also considered.

The deadline for proposals submission is April 30, 2024. 

More at: cssociety.org

Sonia Kéfi, Alexandre Génin, Angeles Garcia-Mayor, Emilio Guirado, Juliano S. Cabral, Miguel Berdugo, Josquin Guerber, Ricard Solé, and Fernando T. Maestre

The spatial structure of vegetation in dryland ecosystems has long fascinated scientists due to its striking appearance. Through a combination of global field surveys, mathematical models, and remote sensing, we show that the mechanisms responsible for these patterns enable healthy dryland ecosystems to adapt to changing environmental conditions, including water shortages, by adjusting their spatial structure. Conversely, degraded ecosystems do not have this ability. Our findings underscore the critical role of spatial pattern formation in promoting resilience in dryland ecosystems. Moreover, these spatial patterns could serve as valuable indicators of ecosystem health under a changing climate, opening important perspectives for future research in this field.

Read the full article at: www.pnas.org