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Extreme Philosophy: Bold Ideas and a Spirit of Progress, edited by Stephen Hetherington

Mon, 03/11/2024 - 16:13

Philosophy’s value and power are greatly diminished when it operates within a too closely confined professional space. Extreme Philosophy: Bold Ideas and a Spirit of Progress serves as an antidote to the increasing narrowness of the field. It offers readers–including students and general readers–twenty internationally acclaimed philosophers who highlight and defend odd, extreme, or ‘mad’ ideas. The resulting conjectures are often provocative and bold, but always clear and accessible.
Ideas discussed in the book, include:
propaganda need not be irrational
science need not be rational
extremism need not be bad
tax evasion need not be immoral
anarchy need not be uninviting
democracy need not remain as it generally is
humans might have immaterial souls
human minds might have all-but-unlimited powers
knowing might be nothing beyond being correct
space and time might not be ‘out there’ in reality
value might be the foundational part of reality
value might differ in an infinitely repeating reality
reality is One
reality is vague
In brief, the volume pursues adventures in philosophy. This spirit of philosophical risk-taking and openness to new, ‘large’ ideas were vital to philosophy’s ancient origins, and they may also be fertile ground today for philosophical progress.

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Cell reprogramming design by transfer learning of functional transcriptional networks

Mon, 03/11/2024 - 12:14

Thomas P. Wytock and Adilson E. Motter

PNAS 121 (11) e2312942121

The lack of genome-wide mathematical models for the gene regulatory network complicates the application of control theory to manipulate cell behavior in humans. We address this challenge by developing a transfer learning approach that leverages genome-wide transcriptomic profiles to characterize cell type attractors and perturbation responses. These responses are used to predict a combinatorial perturbation that minimizes the transcriptional difference between an initial and target cell type, bringing the regulatory network to the target cell type basin of attraction. We anticipate that this approach will enable the rapid identification of potential targets for treatment of complex diseases, while also providing insight into how the dynamics of gene regulatory networks affect phenotype.
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Discord in the voter model for complex networks

Mon, 03/11/2024 - 10:51

Antoine Vendeville, Shi Zhou, and Benjamin Guedj
Phys. Rev. E 109, 024312

Online social networks have become primary means of communication. As they often exhibit undesirable effects such as hostility, polarization, or echo chambers, it is crucial to develop analytical tools that help us better understand them. In this paper we are interested in the evolution of discord in social networks. Formally, we introduce a method to calculate the probability of discord between any two agents in the multistate voter model with and without zealots. Our work applies to any directed, weighted graph with any finite number of possible opinions, allows for various update rates across agents, and does not imply any approximation. Under certain topological conditions, the opinions are independent and the joint distribution can be decoupled. Otherwise, the evolution of discord probabilities is described by a linear system of ordinary differential equations. We prove the existence of a unique equilibrium solution, which can be computed via an iterative algorithm. The classical definition of active links density is generalized to take into account long-range, weighted interactions. We illustrate our findings on real-life and synthetic networks. In particular, we investigate the impact of clustering on discord and uncover a rich landscape of varied behaviors in polarized networks. This sheds lights on the evolution of discord between, and within, antagonistic communities.

Bumblebees socially learn behaviour too complex to innovate alone

Sun, 03/10/2024 - 12:38

Alice D. Bridges, Amanda Royka, Tara Wilson, Charlotte Lockwood, Jasmin Richter, Mikko Juusola & Lars Chittka
Nature (2024)

Culture refers to behaviours that are socially learned and persist within a population over time. Increasing evidence suggests that animal culture can, like human culture, be cumulative: characterized by sequential innovations that build on previous ones1. However, human cumulative culture involves behaviours so complex that they lie beyond the capacity of any individual to independently discover during their lifetime1,2,3. To our knowledge, no study has so far demonstrated this phenomenon in an invertebrate. Here we show that bumblebees can learn from trained demonstrator bees to open a novel two-step puzzle box to obtain food rewards, even though they fail to do so independently. Experimenters were unable to train demonstrator bees to perform the unrewarded first step without providing a temporary reward linked to this action, which was removed during later stages of training. However, a third of naive observer bees learned to open the two-step box from these demonstrators, without ever being rewarded after the first step. This suggests that social learning might permit the acquisition of behaviours too complex to ‘re-innovate’ through individual learning. Furthermore, naive bees failed to open the box despite extended exposure for up to 24 days. This finding challenges a common opinion in the field: that the capacity to socially learn behaviours that cannot be innovated through individual trial and error is unique to humans.

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An “Opinion Reproduction Number” for Infodemics in a Bounded-Confidence Content-Spreading Process on Networks

Sat, 03/09/2024 - 16:56

Heather Z. Brooks, Mason A. Porter

We study the spreading dynamics of content on networks. To do this, we use a model in which content spreads through a bounded-confidence mechanism. In a bounded-confidence model (BCM) of opinion dynamics, the agents of a network have continuous-valued opinions, which they adjust when they interact with agents whose opinions are sufficiently close to theirs. The employed content-spread model introduces a twist into BCMs by using bounded confidence for the content spread itself. To study the spread of content, we define an analogue of the basic reproduction number from disease dynamics that we call an \emph{opinion reproduction number}. A critical value of the opinion reproduction number indicates whether or not there is an “infodemic” (i.e., a large content-spreading cascade) of content that reflects a particular opinion. By determining this critical value, one can determine whether or not an opinion will die off or propagate widely as a cascade in a population of agents. Using configuration-model networks, we quantify the size and shape of content dissemination using a variety of summary statistics, and we illustrate how network structure and spreading model parameters affect these statistics. We find that content spreads most widely when the agents have large expected mean degree or large receptiveness to content. When the amount of content spread only slightly exceeds the critical opinion reproduction number (i.e., the infodemic threshold), there can be longer dissemination trees than when the expected mean degree or receptiveness is larger, even though the total number of content shares is smaller.

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Emergence of innovations in networked populations with reputation-driven interactions

Sat, 03/09/2024 - 12:39

Pablo Gallarta-Sáenz, Hugo Pérez-Martínez,  Jesús Gómez-Gardeñes

Chaos 34, 033106 (2024)

In this work, we analyze how reputation-based interactions influence the emergence of innovations. To do so, we make use of a dynamic model that mimics the discovery process by which, at each time step, a pair of individuals meet and merge their knowledge to eventually result in a novel technology of higher value. The way in which these pairs are brought together is found to be crucial for achieving the highest technological level. Our results show that when the influence of reputation is weak or moderate, it induces an acceleration of the discovery process with respect to the neutral case (purely random coupling). However, an excess of reputation is clearly detrimental, because it leads to an excessive concentration of knowledge in a small set of people, which prevents a diversification of the technologies discovered and, in addition, leads to societies in which a majority of individuals lack technical capabilities.

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Intercity connectivity and urban innovation

Sat, 03/09/2024 - 07:52

Xiaofan Liang, César A. Hidalgo, Pierre-Alexandre Balland, Siqi Zheng, Jianghao Wang

Computers, Environment and Urban Systems Volume 109, April 2024, 102092

Urban outputs, from economy to innovation, are known to grow as a power of a city’s population. But, since large cities tend to be central in transportation and communication networks, the effects attributed to city size may be confounded with those of intercity connectivity. Here, we map intercity networks for the world’s two largest economies (the United States and China) to explore whether a city’s position in the networks of communication, human mobility, and scientific collaboration explains variance in a city’s patenting activity that is unaccounted for by its population. We find evidence that models incorporating intercity connectivity outperform population-based models and exhibit stronger predictive power for patenting activity, particularly for technologies of more recent vintage (which we expect to be more complex or sophisticated). The effects of intercity connectivity are more robust in China, even after controlling for population, GDP, and education, but not in the United States once adjusted for GDP and education. This divergence suggests distinct urban network dynamics driving innovation in these regions. In China, models with social media and mobility networks explain more heterogeneity in the scaling of innovation, whereas in the United States, scientific collaboration plays a more significant role. These findings support the significance of a city’s position within the intercity network in shaping its success in innovative activities.

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Network topology mapping of chemical compounds space

Fri, 03/08/2024 - 18:57

Georgios Tsekenis, Giulio Cimini, Marinos Kalafatis, Achille Giacometti, Tommaso Gili & Guido Caldarelli
Scientific Reports volume 14, Article number: 5266 (2024)

We define bipartite and monopartite relational networks of chemical elements and compounds using two different datasets of inorganic chemical and material compounds, as well as study their topology. We discover that the connectivity between elements and compounds is distributed exponentially for materials, and with a fat tail for chemicals. Compounds networks show similar distribution of degrees, and feature a highly-connected club due to oxygen . Chemical compounds networks appear more modular than material ones, while the communities detected reveal different dominant elements specific to the topology. We successfully reproduce the connectivity of the empirical chemicals and materials networks by using a family of fitness models, where the fitness values are derived from the abundances of the elements in the aggregate compound data. Our results pave the way towards a relational network-based understanding of the inherent complexity of the vast chemical knowledge atlas, and our methodology can be applied to other systems with the ingredient-composite structure.

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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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