Complexity Digest

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LLM Voting: Human Choices and AI Collective Decision Making

Fri, 03/08/2024 - 14:54

Joshua C. Yang, Marcin Korecki, Damian Dailisan, Carina I. Hausladen, Dirk Helbing

This paper investigates the voting behaviors of Large Language Models (LLMs), particularly OpenAI’s GPT4 and LLaMA2, and their alignment with human voting patterns. Our approach included a human voting experiment to establish a baseline for human preferences and a parallel experiment with LLM agents. The study focused on both collective outcomes and individual preferences, revealing differences in decision-making and inherent biases between humans and LLMs. We observed a trade-off between preference diversity and alignment in LLMs, with a tendency towards more uniform choices as compared to the diverse preferences of human voters. This finding indicates that LLMs could lead to more homogenized collective outcomes when used in voting assistance, underscoring the need for cautious integration of LLMs into democratic processes.

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A nonadaptive explanation for macroevolutionary patterns in the evolution of complex multicellularity

Fri, 03/08/2024 - 14:51

Emma P. Bingham and William C. Ratcliff

PNAS 121 (7) e2319840121

“Complex multicellularity,” conventionally defined as large organisms with many specialized cell types, has evolved five times independently in eukaryotes, but never within prokaryotes. A number of hypotheses have been proposed to explain this phenomenon, most of which posit that eukaryotes evolved key traits (e.g., dynamic cytoskeletons, alternative mechanisms of gene regulation, or subcellular compartments) which were a necessary prerequisite for the evolution of complex multicellularity. Here, we propose an alternative, nonadaptive hypothesis for this broad macroevolutionary pattern. By binning cells into groups with finite genetic bottlenecks between generations, the evolution of multicellularity greatly reduces the effective population size (Ne) of cellular populations, increasing the role of genetic drift in evolutionary change. While both prokaryotes and eukaryotes experience this phenomenon, they have opposite responses to drift: eukaryotes tend to undergo genomic expansion, providing additional raw genetic material for subsequent multicellular innovation, while prokaryotes generally face genomic erosion. Taken together, we hypothesize that these idiosyncratic lineage-specific evolutionary dynamics play a fundamental role in the long-term divergent evolution of complex multicellularity across the tree of life.

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Traffic & Granular Flow 2024

Fri, 03/08/2024 - 12:41

The 15th edition of Traffic and Granular Flow (TGF) will be held in Lyon, France, from December 2nd to December 5th 2024. In-person participation will be favoured.

The international conference on TGF has been held biennially in different parts of the world since 1995. The conference is especially designed for an interdisciplinary audience working in the area of physics, computer sciences, engineering, granular, vehicular and pedestrian flow.

It focuses on giving a global perspective on the latest developments and new ideas in traffic and granular flows broadly speaking which encompasses the fields of granular flow, pedestrian dynamics, collective animal behaviour, and  urban mobility.

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The 15-minute city quantified using human mobility data

Wed, 03/06/2024 - 11:10

Timur Abbiasov, Cate Heine, Sadegh Sabouri, Arianna Salazar-Miranda, Paolo Santi, Edward Glaeser & Carlo Ratti
Nature Human Behaviour (2024)

Amid rising congestion and transport emissions, policymakers are embracing the ‘15-minute city’ model, which envisions neighbourhoods where basic needs can be met within a short walk from home. Prior research has primarily examined amenity access without exploring its relationship to behaviour. We introduce a measure of local trip behaviour using GPS data from 40 million US mobile devices, defining ‘15-minute usage’ as the proportion of consumption-related trips made within a 15-minute walk from home. Our findings show that the median resident makes only 14% of daily consumption trips locally. Differences in access to local amenities can explain 84% and 74% of the variation in 15-minute usage across and within urban areas, respectively. Historical data from New York zoning policies suggest a causal relationship between local access and 15-minute usage. However, we find a trade-off: increased local usage correlates with higher experienced segregation for low-income residents, signalling potential socio-economic challenges in achieving local living.

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Modelling the creation of friends and foes groups in small real social networks

Tue, 03/05/2024 - 18:11

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.

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An ability to respond begins with inner alignment: How phase synchronisation effects transitions to higher levels of agency

Tue, 03/05/2024 - 09:38

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.

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Stochastic regimes can hide the attractors in data, reconstruction algorithms can reveal them

Mon, 03/04/2024 - 18:03

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.

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WCCS24 | World Conference on Complex Systems

Mon, 03/04/2024 - 10:17

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..

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All Crises are Unhappy in their Own Way: The role of societal instability in shaping the past

Sun, 03/03/2024 - 11:15

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.

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Software in the natural world: A computational approach to emergence in complex multi-level systems

Sat, 03/02/2024 - 13:25

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.

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Cultural Evolution, Disinformation, and Social Division

Sat, 03/02/2024 - 10:16

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.

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A synthetic microbial Daisyworld: planetary regulation in the test tube

Fri, 03/01/2024 - 13:23

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.

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Complex networks with complex weights

Fri, 03/01/2024 - 11:03

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.

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Brains Are Not Required When It Comes to Thinking and Solving Problems–Simple Cells Can Do It

Thu, 02/29/2024 - 11:08

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

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What ALife! Podcast Episode 01: Hiroki Sayama

Wed, 02/28/2024 - 13:09

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 (…2021/33/21/102961)

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Unsupervised Embedding of Trajectories Captures the Latent Structure of Scientific Migration

Wed, 02/28/2024 - 12:28

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”

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Emergence of a synergistic scaffold in the brains of human infants

Wed, 02/28/2024 - 11:05

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

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School on Modelling Infectious Disease Dynamics.  May 6 – 12, 2024.  São Paulo, Brazil

Tue, 02/27/2024 - 10:02

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.

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Principled Limitations on Self-Representation for Generic Physical Systems

Tue, 02/27/2024 - 09:40

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.

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Complexity Global School | Santa Fe Institute

Mon, 02/26/2024 - 16:52

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.

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