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Cultivating creativity: predictive brains and the enlightened room problem

Complexity Digest - Thu, 12/21/2023 - 15:12

Axel Constant , Karl John Friston and Andy Clark

Philosophical Transactions of the Royal Society B Volume 379 Issue 1895

How can one conciliate the claim that humans are uncertainty minimizing systems that seek to navigate predictable and familiar environments with the claim that humans can be creative? We call this the Enlightened Room Problem (ERP). The solution, we suggest, lies not (or not only) in the error-minimizing brain but in the environment itself. Creativity emerges from various degrees of interplay between predictive brains and changing environments: ones that repeatedly move the goalposts for our own error-minimizing machinery. By (co)constructing these challenging worlds, we effectively alter and expand the space within which our own prediction engines operate, and that function as ‘exploration bubbles’ that enable information seeking, uncertainty minimizing minds to penetrate deeper and deeper into artistic, scientific and engineering space. In what follows, we offer a proof of principle for this kind of environmentally led cognitive expansion.

Read the full article at: royalsocietypublishing.org

Making mind matter with irruption theory: Bridging end-directedness and entropy production by satisfying the participation criterion

Complexity Digest - Thu, 12/21/2023 - 13:46

Froese, Tom and Georgii, Karelin and Takashi, Ikegami

Biological processes are end-directed, that is, teleological. Explaining the physical efficacy of end-directedness continues to be a profound challenge for theoretical biology, especially given its unavoidable implications for our own self-understanding. For a comprehensive theory of life, it is pivotal to bridge our human-centric view of end-directedness, which the social sciences and humanities consider intrinsic to our actions, with the natural sciences’ view of actions’ in purely physiological terms, especially in terms of thermodynamic tendencies. A comprehensive theory should therefore provide an end-involving account, which illuminates how both physiology and teleology distinctly contribute to behavior generation. Here we introduce the “Participation Criterion”: End-involvement in a bodily process entails that, in principle, it is distinguishable from one without end-involvement, specifically in terms of physiologically unpredictable changes in unexplainable variability. To exemplify the difficulty of satisfying this criterion, we critically analyze two theories on the thermodynamic basis of end-directedness. We then propose that “Irruption Theory” points to a way forward because it predicts that bodily processes have an end-involvement-dependent increase in their entropy rate. This is consistent with evidence of an association between conscious intention and neural fluctuations, is open to further experimental verification, and provides a novel perspective on the role of thermodynamic entropy production in the organism.

Read the full article at: philsci-archive.pitt.edu

Multistable Protocells Can Aid the Evolution of Prebiotic Autocatalytic Sets

Complexity Digest - Thu, 12/21/2023 - 09:01

Angad Yuvraj Singh and Sanjay Jain

We present a simple mathematical model that captures the evolutionary capabilities of a prebiotic compartment or protocell. In the model, the protocell contains an autocatalytic set whose chemical dynamics is coupled to the growth–division dynamics of the compartment. Bistability in the dynamics of the autocatalytic set results in a protocell that can exist with two distinct growth rates. Stochasticity in chemical reactions plays the role of mutations and causes transitions from one growth regime to another. We show that the system exhibits ‘natural selection’, where a ‘mutant’ protocell in which the autocatalytic set is active arises by chance in a population of inactive protocells, and then takes over the population because of its higher growth rate or ‘fitness’. The work integrates three levels of dynamics: intracellular chemical, single protocell, and population (or ecosystem) of protocells.

Read the full article at: www.mdpi.com

The structure of segregation in co-authorship networks and its impact on scientific production

Complexity Digest - Wed, 12/20/2023 - 15:52

Ana Maria Jaramillo, Hywel T. P. Williams, Nicola Perra & Ronaldo Menezes 

EPJ Data Science volume 12, Article number: 47 (2023)

Co-authorship networks, where nodes represent authors and edges represent co-authorship relations, are key to understanding the production and diffusion of knowledge in academia. Social constructs, biases (implicit and explicit), and constraints (e.g. spatial, temporal) affect who works with whom and cause co-authorship networks to organise into tight communities with different levels of segregation. We aim to examine aspects of the co-authorship network structure that lead to segregation and its impact on scientific production. We measure segregation using the Spectral Segregation Index (SSI) and find four ordered categories: completely segregated, highly segregated, moderately segregated and non-segregated communities. We direct our attention to the non-segregated and highly segregated communities, quantifying and comparing their structural topologies and k-core positions. When considering communities of both categories (controlling for size), our results show no differences in density and clustering but substantial variability in the core position. Larger non-segregated communities are more likely to occupy cores near the network nucleus, while the highly segregated ones tend to be closer to the network periphery. Finally, we analyse differences in citations gained by researchers within communities of different segregation categories. Researchers in highly segregated communities get more citations from their community members in middle cores and gain more citations per publication in middle/periphery cores. Those in non-segregated communities get more citations per publication in the nucleus. To our knowledge, this work is the first to characterise community segregation in co-authorship networks and investigate the relationship between community segregation and author citations. Our results help study highly segregated communities of scientific co-authors and can pave the way for intervention strategies to improve the growth and dissemination of scientific knowledge.

Read the full article at: epjdatascience.springeropen.com

Mediterranean School of Complex Networks.  Grado, Italy 30 June – 5 July 2024

Complexity Digest - Wed, 12/20/2023 - 12:32

In the last decade, network theory has been revealed to be a perfect instrument to model the structure of complex systems and the dynamical process they are involved into. The wide variety of applications to social sciences, technological networks, biology, transportation and economic, to cite just only some of them, showed that network theory is suitable to provide new insights into many problems.
Given the success of the Eighth Edition in 2023 of the Mediterranean School of Complex Networks, we call for applications to the Ninth Edition in 2024.

More at: mediterraneanschoolcomplex.net

Models of Cell Processes are Far from the Edge of Chaos

Complexity Digest - Tue, 12/19/2023 - 12:50

Kyu Hyong Park, Felipe Xavier Costa, Luis M. Rocha, Réka Albert, and Jordan C. Rozum
PRX Life 1, 023009

Complex living systems are thought to exist at the “edge of chaos” separating the ordered dynamics of robust function from the disordered dynamics of rapid environmental adaptation. Here, a deeper inspection of 72 experimentally supported discrete dynamical models of cell processes reveals previously unobserved order on long time scales, suggesting greater rigidity in these systems than was previously conjectured. We find that propagation of internal perturbations is transient in most cases, and that even when large perturbation cascades persist, their phenotypic effects are often minimal. Moreover, we find evidence that stochasticity and desynchronization can lead to increased recovery from regulatory perturbation cascades. Our analysis relies on new measures that quantify the tendency of perturbations to spread through a discrete dynamical system. Computing these measures was not feasible using current methodology; thus, we developed a multipurpose CUDA-based simulation tool, which we have made available as the open-source Python library cubewalkers. Based on novel measures and simulations, our results suggest that—contrary to current theory—cell processes are ordered and far from the edge of chaos.

Read the full article at: link.aps.org

The Evolution of Biological Information: How Evolution Creates Complexity, from Viruses to Brains: Christoph Adami

Complexity Digest - Mon, 12/18/2023 - 18:41

Why information is the unifying principle that allows us to understand the evolution of complexity in nature

More than 150 years after Darwin’s revolutionary On the Origin of Species, we are still attempting to understand and explain the amazing complexity of life. Although we now know how evolution proceeds to build complexity from simple ingredients, quantifying this complexity is still a difficult undertaking. In this book, Christoph Adami offers a new perspective on Darwinian evolution by viewing it through the lens of information theory. This novel theoretical stance sheds light on such matters as how viruses evolve drug resistance, how cells evolve to communicate, and how intelligence evolves. By this account, information emerges as the central unifying principle behind all of biology, allowing us to think about the origin of life—on Earth and elsewhere—in a systematic manner.

Adami, a leader in the field of computational biology, first provides an accessible introduction to the information theory of biomolecules and then shows how to apply these tools to measure information stored in genetic sequences and proteins. After outlining the experimental evidence of the evolution of information in both bacteria and digital organisms, he describes the evolution of robustness in viruses; the cooperation among cells, animals, and people; and the evolution of brains and intelligence. Building on extensive prior work in bacterial and digital evolution, Adami establishes that (expanding on Dobzhansky’s famous remark) nothing in biology makes sense except in the light of information. Understanding that information is the foundation of all life, he argues, allows us to see beyond the particulars of our way of life to glimpse what life might be like in other worlds.

Read the full article at: press.princeton.edu

Analysis of International Economic Integration based on a Computational Mathematical Model of Economic Complexity

Complexity Digest - Mon, 12/18/2023 - 17:51

Arturo González, et al.

2023 XLIX Latin American Computer Conference (CLEI)

International Economic Integration entails collaborative efforts among nations to overcome barriers and achieve shared benefits. The development of analytical models is crucial for comprehending the interaction of countries as a collective entity. In South America, MERCOSUR stands out, comprising Argentina, Brazil, Paraguay, and Uruguay. In this study, Economic Complexity metrics were applied to analyze productive capacities within MERCOSUR. The results underscore integration’s significance by forming economic blocs, capabilities are expanded, enriching diversity and the scope of production. Economic complexity serves as a pivotal tool for assessing interdependence and enhancing countries’ global positioning. In summary, this work highlights how economic integration, exemplified by MERCOSUR, enhances productive capacity, propelling development, and competitiveness in an interconnected world. Leveraging a novel computational mathematical model, this study offers insights into the complex dynamics of international economic integration, shedding light on strategies to foster growth and collaboration in a rapidly evolving global landscape.

Read the full article at: ieeexplore.ieee.org

On the roles of function and selection in evolving systems

Complexity Digest - Sun, 12/17/2023 - 18:36

Michael L. Wong, et al.

The universe is replete with complex evolving systems, but the existing macroscopic physical laws do not seem to adequately describe these systems. Recognizing that the identification of conceptual equivalencies among disparate phenomena were foundational to developing previous laws of nature, we approach a potential “missing law” by looking for equivalencies among evolving systems. We suggest that all evolving systems—including but not limited to life—are composed of diverse components that can combine into configurational states that are then selected for or against based on function. We then identify the fundamental sources of selection—static persistence, dynamic persistence, and novelty generation—and propose a time-asymmetric law that states that the functional information of a system will increase over time when subjected to selection for function(s).

Read the full article at: www.pnas.org

Emergence of Scale-Free Networks in Social Interactions among Large Language Models

Complexity Digest - Sat, 12/16/2023 - 18:25

Giordano De Marzo, Luciano Pietronero, David Garcia

Scale-free networks are one of the most famous examples of emergent behavior and are ubiquitous in social systems, especially online social media in which users can follow each other. By analyzing the interactions of multiple generative agents using GPT3.5-turbo as a language model, we demonstrate their ability to not only mimic individual human linguistic behavior but also exhibit collective phenomena intrinsic to human societies, in particular the emergence of scale-free networks. We discovered that this process is disrupted by a skewed token prior distribution of GPT3.5-turbo, which can lead to networks with extreme centralization as a kind of alignment. We show how renaming agents removes these token priors and allows the model to generate a range of networks from random networks to more realistic scale-free networks.

Read the full article at: arxiv.org

The unequal effects of the health–economy trade-off during the COVID-19 pandemic

Complexity Digest - Fri, 12/15/2023 - 20:43

Marco Pangallo, Alberto Aleta, R. Maria del Rio-Chanona, Anton Pichler, David Martín-Corral, Matteo Chinazzi, François Lafond, Marco Ajelli, Esteban Moro, Yamir Moreno, Alessandro Vespignani & J. Doyne Farmer
Nature Human Behaviour (2023)

Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simulates epidemic and economic outcomes across industries, occupations and income levels. We validate the model by reproducing key outcomes of the first wave of coronavirus disease 2019 in the New York metropolitan area. The key mechanism coupling the epidemic and economic modules is the reduction in consumption due to fear of infection. In counterfactual experiments, we show that a similar trade-off between epidemic and economic outcomes exists both when individuals change their behaviour due to fear of infection and when non-pharmaceutical interventions are imposed. Low-income workers, who perform in-person occupations in customer-facing industries, face the strongest trade-off.

Read the full article at: www.nature.com

Why birds are smart

Complexity Digest - Fri, 12/15/2023 - 18:23

Onur Güntürkün, Roland Pusch, Jonas Rose

Trends in Cognitive Sciences

Many cognitive neuroscientists believe that both a large brain and an isocortex are
crucial for complex cognition. Yet corvids and parrots possess non-cortical brains
of just 1–25 g, and these birds exhibit cognitive abilities comparable with those
of great apes such as chimpanzees, which have brains of about 400 g. This opinion
explores how this cognitive equivalence is possible. We propose four features that
may be required for complex cognition: a large number of associative pallial neurons,
a prefrontal cortex (PFC)-like area, a dense dopaminergic innervation of association
areas, and dynamic neurophysiological fundaments for working memory. These four neural
features have convergently evolved and may therefore represent ‘hard to replace’ mechanisms
enabling complex cognition.

Read the full article at: www.cell.com

Models of Cell Processes are Far from the Edge of Chaos

Complexity Digest - Fri, 12/15/2023 - 12:22

Kyu Hyong Park, Felipe Xavier Costa, Luis M. Rocha, Réka Albert, and Jordan C. Rozum

PRX Life 1, 023009 – Published 15 December 2023

Complex living systems are thought to exist at the “edge of chaos” separating the ordered dynamics of robust function from the disordered dynamics of rapid environmental adaptation. Here, a deeper inspection of 72 experimentally supported discrete dynamical models of cell processes reveals previously unobserved order on long time scales, suggesting greater rigidity in these systems than was previously conjectured. We find that propagation of internal perturbations is transient in most cases, and that even when large perturbation cascades persist, their phenotypic effects are often minimal. Moreover, we find evidence that stochasticity and desynchronization can lead to increased recovery from regulatory perturbation cascades. Our analysis relies on new measures that quantify the tendency of perturbations to spread through a discrete dynamical system. Computing these measures was not feasible using current methodology; thus, we developed a multipurpose CUDA-based simulation tool, which we have made available as the open-source Python library cubewalkers. Based on novel measures and simulations, our results suggest that—contrary to current theory—cell processes are ordered and far from the edge of chaos.

Read the full article at: link.aps.org

Understanding political divisiveness using online participation data from the 2022 French and Brazilian presidential elections | Nature Human Behaviour

Complexity Digest - Thu, 12/14/2023 - 20:47

Carlos Navarrete, Mariana Macedo, Rachael Colley, Jingling Zhang, Nicole Ferrada, Maria Eduarda Mello, Rodrigo Lira, Carmelo Bastos-Filho, Umberto Grandi, Jérôme Lang & César A. Hidalgo 

Nature Human Behaviour (2023)

Digital technologies can augment civic participation by facilitating the expression of detailed political preferences. Yet, digital participation efforts often rely on methods optimized for elections involving a few candidates. Here we present data collected in an online experiment where participants built personalized government programmes by combining policies proposed by the candidates of the 2022 French and Brazilian presidential elections. We use this data to explore aggregates complementing those used in social choice theory, finding that a metric of divisiveness, which is uncorrelated with traditional aggregation functions, can identify polarizing proposals. These metrics provide a score for the divisiveness of each proposal that can be estimated in the absence of data on the demographic characteristics of participants and that explains the issues that divide a population. These findings suggest that divisiveness metrics can be useful complements to traditional aggregation functions in direct forms of digital participation.

Read the full article at: www.nature.com

The clinical trials puzzle: How network effects limit drug discovery

Complexity Digest - Thu, 12/14/2023 - 18:35

KISHORE VASAN, DEISY MORSELLI GYSI, ALBERT-LÁSZLÓ BARABÁSI

iScience 26, 108361

The depth of knowledge offered by post-genomic medicine has carried the promise of new drugs, and cures for multiple diseases. To explore the degree to which this capability has materialized, we extract meta-data from 356,403 clinical trials spanning four decades, aiming to offer mechanistic insights into the innovation practices in drug discovery. We find that convention dominates over innovation, as over 96% of the recorded trials focus on previously tested drug targets, and the tested drugs target only 12% of the human interactome. If current patterns persist, it would take 170 years to target all druggable proteins. We uncover two network-based fundamental mechanisms that currently limit target discovery: preferential attachment, leading to the repeated exploration of previously targeted proteins; and local network effects, limiting exploration to proteins interacting with highly explored proteins. We build on these insights to develop a quantitative network-based model to enhance drug discovery in clinical trials.

Read the full article at: www.cell.com

Call for Tutors – Complexity72h (Madrid, Spain, June 24th to 28th)

Complexity Digest - Wed, 12/13/2023 - 13:48

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 Tutors is currently open until January 8th*.

Individuals interested in tutoring during the workshop should apply by submitting an abstract of the proposed project. While the project doesn’t need to be fully developed at this stage, applicants should provide a clear idea of their focus, list the required data, and be prepared to supply it to participants. These projects will be undertaken by a group of approximately 6-8 workshop participants.

Tutors will receive accommodation and meals for the entire five days, and travel expenses may be partially or fully covered based on the budget. All relevant information can be found at https://complexity72h.com/call-for-tutors/.

If you are interested in becoming a tutor and leading a project, please don’t hesitate to apply and spread the word among your fellow researchers and mentors!

More at: complexity72h.com

Postdoctoral Positions at the Center for Network Dynamics, Northwestern University

Complexity Digest - Tue, 12/12/2023 - 11:41

The newly launched Center for Network Dynamics at Northwestern University is actively seeking postdoctoral researchers interested in complex systems and networks. We welcome applications from individuals with expertise in various aspects of network theory, including temporal, multilayer, and higher-order interactions. Additionally, we are seeking applicants with interest in network modeling of biological, physical, and engineering systems. The projects are theoretical and computational but benefit from empirical data and close collaborations with experimental colleagues. If you are passionate about advancing the understanding of networks and their applications in diverse fields, we encourage you to apply to our dynamic research team. For information on how to apply, please visit cnd.northwestern.edu

French Regional Conference on Complex Systems FRCCS 2024. May 29-31, Montpellier, France

Complexity Digest - Tue, 12/12/2023 - 10:52

FRCCS 2024 is the 4th edition of the French Regional Conference on Complex Systems. It aims at bringing together the French scientific community working in complex systems. It intends to federate the French community.
We encourage researchers from various disciplines supporting interdisciplinary exchanges to respond to this call (archaeology, biology, computer science, economics, geography, history, linguistics, management, mathematics, medicine, physics, statistics, sociology, …). FRCCS 2024 is an opportunity to promote the cross-fertilization of ideas by presenting recent research work, industrial developments, and original applications. Special attention is given to research topics with a high societal impact from the perspective of complexity science from the complexity science perspective.

More at: iutdijon.u-bourgogne.fr

Towards self‐organizing logistics in transportation: a literature review and typology

Complexity Digest - Thu, 12/07/2023 - 10:56

Berry Gerrits, Wouter van Heeswijk, Martijn Mes

Intl. Trans. in Op. Res. 0 (2023) 1–66

Deploying self-organizing systems is a way to cope with the logistics sector’s complex, dynamic, and stochastic nature. In such systems, automated decision-making and decentralized or distributed control structures are combined. Such control structures reduce the complexity of decision-making, require less computational effort, and are therefore faster, reducing the risk that changes during decision-making render the solution invalid. These benefits of self-organizing systems are of interest to many practitioners involved in solving real-world problems in the logistics sector. This study, therefore, identifies and classifies research related to self-organizing logistics (SOL) with a focus on transportation. SOL is an interdisciplinary study across many domains and relates to other concepts, such as agent-based systems, autonomous control, and decentral systems. Yet, few papers directly identify this as self-organization. Hence, we add to the existing literature by conducting a systematic literature review that provides insight into the field of SOL. The main contribution of this paper is two-fold: (i) based on the findings from the literature review, we identify and synthesize 15 characteristics of SOL in a typology, and (ii) we present a two-dimensional SOL framework alongside the axes of autonomy and cooperativity to position and contrast the broad range of literature, thereby creating order in the field of SOL and revealing promising research directions.

Read the full article at: onlinelibrary.wiley.com

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