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Melanie Mitchell Takes AI Research Back to Its Roots

Complexity Digest - Wed, 04/21/2021 - 14:03

To build a general artificial intelligence, we may need to know more about our own minds, argues the computer scientist Melanie Mitchell.

Full episode at: www.quantamagazine.org

Phase transitions and assortativity in models of gene regulatory networks evolved under different selection processes

Complexity Digest - Tue, 04/20/2021 - 15:13

Brandon Alexander , Alexandra Pushkar and Michelle Girvan

Journal of the Royal Society Interface Volume 18 Issue 177

We study a simplified model of gene regulatory network evolution in which links (regulatory interactions) are added via various selection rules that are based on the structural and dynamical features of the network nodes (genes). Similar to well-studied models of ‘explosive’ percolation, in our approach, links are selectively added so as to delay the transition to large-scale damage propagation, i.e. to make the network robust to small perturbations of gene states. We find that when selection depends only on structure, evolved networks are resistant to widespread damage propagation, even without knowledge of individual gene propensities for becoming ‘damaged’. We also observe that networks evolved to avoid damage propagation tend towards disassortativity (i.e. directed links preferentially connect high degree ‘source’ genes to low degree ‘target’ genes and vice versa). We compare our simulations to reconstructed gene regulatory networks for several different species, with genes and links added over evolutionary time, and we find a similar bias towards disassortativity in the reconstructed networks.

Read the full article at: royalsocietypublishing.org

“Too Lazy”: Episode 2 with Roberta Sinatra –

Complexity Digest - Tue, 04/20/2021 - 14:02

Today is Roberta Sinatra day on #TooLazyPod!! Roberta is a physicist, an expert on science of success, and all-round fantastic person. In the podcast, we talks about her recent paper “Success and luck in creative careers”.

Full episode at: sunelehmann.com

Time to regulate AI that interprets human emotions

Complexity Digest - Sun, 04/18/2021 - 07:26

The pandemic is being used as a pretext to push unproven artificial-intelligence tools into workplaces and schools.

Read the full article at: www.nature.com

The COVID-19 Infodemic: Twitter versus Facebook

Complexity Digest - Sat, 04/17/2021 - 07:24

Kai-Cheng Yang, Francesco Pierri, Pik-Mai Hui, David Axelrod, Christopher Torres-Lugo, John Bryden, Filippo Menczer

The global spread of the novel coronavirus is affected by the spread of related misinformation — the so-called COVID-19 Infodemic — that makes populations more vulnerable to the disease through resistance to mitigation efforts. Here we analyze the prevalence and diffusion of links to low-credibility content about the pandemic across two major social media platforms, Twitter and Facebook. We characterize cross-platform similarities and differences in popular sources, diffusion patterns, influencers, coordination, and automation. Comparing the two platforms, we find divergence among the prevalence of popular low-credibility sources and suspicious videos. A minority of accounts and pages exert a strong influence on each platform. These misinformation “superspreaders” are often associated with the low-credibility sources and tend to be verified by the platforms. On both platforms, there is evidence of coordinated sharing of Infodemic content. The overt nature of this manipulation points to the need for societal-level rather than in-house mitigation strategies. However, we highlight limits imposed by inconsistent data-access policies on our capability to study harmful manipulations of information ecosystems.

Read the full article at: arxiv.org

Modeling COVID-19 for Lifting Non-Pharmaceutical Interventions

Complexity Digest - Fri, 04/16/2021 - 07:21

Matthew Koehler, David M Slater, Garry Jacyna and James R Thompson

Journal of Artificial Societies and Social Simulation 24 (2) 9

As a result of the COVID-19 worldwide pandemic, the United States instituted various non-pharmaceutical interventions (NPIs) in an effort to slow the spread of the disease. Although necessary for public safety, these NPIs can also have deleterious effects on the economy of a nation. State and federal leaders need tools that provide insight into which combination of NPIs will have the greatest impact on slowing the disease and at what point in time it is reasonably safe to start lifting these restrictions to everyday life. In the present work, we outline a modeling process that incorporates the parameters of the disease, the effects of NPIs, and the characteristics of individual communities to offer insight into when and to what degree certain NPIs should be instituted or lifted based on the progression of a given outbreak of COVID-19. We apply the model to the 24 county-equivalents of Maryland and illustrate that different NPI strategies can be employed in different parts of the state. Our objective is to outline a modeling process that combines the critical disease factors and factors relevant to decision-makers who must balance the health of the population with the health of the economy.

Read the full article at: jasss.soc.surrey.ac.uk

Too Lazy to Read the Paper. Episode 1

Complexity Digest - Wed, 04/14/2021 - 13:48

This inaugural episode features physicist, urban planning, human mobility and transportation scientist Marta C. González from UC Berkeley explaining the long and winding road to her paper The TimeGeo modeling framework for urban mobility without travel surveys [1].

In the podcast, we take our time, tracing Marta’s career from Venezuelan graduate student, to postdoc in Germany, Notre Dame (US), and Boston. We hear a bit about what it’s like to be a physicist at MIT’s transportation department … and how all those things shaped Marta’s research and the paper we’re discussing.

View/listen the full episode at: sunelehmann.com

Economics in Nouns and Verbs

Complexity Digest - Tue, 04/13/2021 - 11:55

W. Brian Arthur

Standard economic theory uses mathematics as its main means of understanding,
and this brings clarity of reasoning and logical power. But there is a
drawback: algebraic mathematics restricts economic modeling to what can be
expressed only in quantitative nouns, and this forces theory to leave out
matters to do with process, formation, adjustment, creation and nonequilibrium.
For these we need a different means of understanding, one that allows verbs as
well as nouns. Algorithmic expression is such a means. It allows verbs
(processes) as well as nouns (objects and quantities). It allows fuller
description in economics, and can include heterogeneity of agents, actions as
well as objects, and realistic models of behavior in ill-defined situations.
The world that algorithms reveal is action-based as well as object-based,
organic, possibly ever-changing, and not fully knowable. But it is strangely
and wonderfully alive.

Read the full article at: arxiv.org

Avoiding the bullies: The resilience of cooperation among unequals

Complexity Digest - Mon, 04/12/2021 - 11:20

Foley M, Smead R, Forber P, Riedl C (2021) Avoiding the bullies: The resilience of cooperation among unequals. PLoS Comput Biol 17(4): e1008847.

Individuals often differ in their ability to resolve conflicts in their favor, and this can lead to the emergence of hierarchies and dominant alphas. Such social structures present a serious risk of destabilizing cooperative social interactions or norms. Why work together to find food when a more aggressive or stronger individual can take all of it? In this paper we use game theory and agent-based modeling to investigate how cooperative behavior evolves in the presence of powerful bullies who have no incentive to cooperate. We show that when individuals can choose their interaction partners, bullies do not always destabilize cooperation. Instead, cooperative norms survive as individuals learn to avoid dominant individuals who become isolated in the population. When competitive ability itself depends dynamically on past success, complex cycles of coupled network-strategy-rank changes emerge: effective collaborators gain popularity and thus power, adopt aggressive behavior, get isolated, then lose power. Our results have important implications: in our modeled scenario the rich do not always get richer, the dominance of bullies can be broken, and inequality in accrued resources can be eliminated. Thus, our work provides new insight into potential sources of, and strategies for avoiding, resource inequality.

Read the full article at: journals.plos.org

Cells Form Into ‘Xenobots’ on Their Own

Complexity Digest - Sun, 04/11/2021 - 13:49

Embryonic cells can self-assemble into new living forms that don’t resemble the bodies they usually generate, challenging old ideas of what defines an organism.

Read the full article at: www.quantamagazine.org

See Also: 

A cellular platform for the development of synthetic living machines
Douglas Blackiston, Emma Lederer, Sam Kriegman, Simon Garnier, Joshua Bongard, Michael Levin

Science Robotics 31 Mar 2021:
Vol. 6, Issue 52, eabf1571

Behavioral and Cognitive Robotics: An adaptive perspective

Complexity Digest - Sat, 04/10/2021 - 13:40

Stefano Nolfi

This book describes how to create robots capable to develop the behavioral and cognitive skills required to perform a task autonomously, while they interact with their environment, through evolutionary and/or learning processes. It focuses on model-free approaches with minimal human-designed intervention in which the behavior used by the robot solve its task and the way in which such behavior is produced is discovered by the adaptive process automatically, i.e. it is not specified by the experimenter.

Read the full book at: bacrobotics.com

Emergence of Polarized Ideological Opinions in Multidimensional Topic Spaces

Complexity Digest - Wed, 04/07/2021 - 13:55

Fabian Baumann, Philipp Lorenz-Spreen, Igor M. Sokolov, and Michele Starnini
Phys. Rev. X 11, 011012 (2021)

By embedding opinions in a nonorthogonal topic space, a new model shows that a reinforcement mechanism driven by homophilic social interactions reproduces extreme and correlated opinion states found in surveys.

Read the full article at: link.aps.org

Random Networks with Quantum Boolean Functions

Complexity Digest - Wed, 04/07/2021 - 13:32

Mario Franco, Octavio Zapata, David A. Rosenblueth,  and Carlos Gershenson

Mathematics 2021, 9(8), 792

We propose quantum Boolean networks, which can be classified as deterministic reversible asynchronous Boolean networks. This model is based on the previously developed concept of quantum Boolean functions. A quantum Boolean network is a Boolean network where the functions associated with the nodes are quantum Boolean functions. We study some properties of this novel model and, using a quantum simulator, we study how the dynamics change in function of connectivity of the network and the set of operators we allow. For some configurations, this model resembles the behavior of reversible Boolean networks, while for other configurations a more complex dynamic can emerge. For example, cycles larger than 2N were observed. Additionally, using a scheme akin to one used previously with random Boolean networks, we computed the average entropy and complexity of the networks. As opposed to classic random Boolean networks, where “complex” dynamics are restricted mainly to a connectivity close to a phase transition, quantum Boolean networks can exhibit stable, complex, and unstable dynamics independently of their connectivity.

Read the full article at: www.mdpi.com

The global network of ports supporting high seas fishing | Science Advances

Complexity Digest - Tue, 04/06/2021 - 16:21

Jorge P. Rodríguez, Juan Fernández-Gracia, Carlos M. Duarte, Xabier Irigoien, and Víctor M. Eguíluz

Science Advances 26 Feb 2021:
Vol. 7, no. 9, eabe3470

Fisheries in waters beyond national jurisdiction (“high seas”) are difficult to monitor and manage. Their regulation for sustainability requires critical information on how fishing effort is distributed across fishing and landing areas, including possible border effects at the exclusive economic zone (EEZ) limits. We infer the global network linking harbors supporting fishing vessels to fishing areas in high seas from automatic identification system tracking data in 2014, observing a modular structure, with vessels departing from a given harbor fishing mostly in a single province. The top 16% of these harbors support 84% of fishing effort in high seas, with harbors in low- and middle-income countries ranked among the top supporters. Fishing effort concentrates along narrow strips attached to the boundaries of EEZs with productive fisheries, identifying a free-riding behavior that jeopardizes efforts by nations to sustainably manage their fisheries, perpetuating the tragedy of the commons affecting global fishery resources.

Read the full article at: advances.sciencemag.org

Asymptotic Information-Theoretic Detection of Dynamical Organization in Complex Systems

Complexity Digest - Tue, 04/06/2021 - 13:46

Gianluca D’Addese, Laura Sani, Luca La Rocca, Roberto Serra, and Marco Villani

Entropy 2021, 23(4), 398;

The identification of emergent structures in complex dynamical systems is a formidable challenge. We propose a computationally efficient methodology to address such a challenge, based on modeling the state of the system as a set of random variables. Specifically, we present a sieving algorithm to navigate the huge space of all subsets of variables and compare them in terms of a simple index that can be computed without resorting to simulations. We obtain such a simple index by studying the asymptotic distribution of an information-theoretic measure of coordination among variables, when there is no coordination at all, which allows us to fairly compare subsets of variables having different cardinalities. We show that increasing the number of observations allows the identification of larger and larger subsets. As an example of relevant application, we make use of a paradigmatic case regarding the identification of groups in autocatalytic sets of reactions, a chemical situation related to the origin of life problem.

Read the full article at: www.mdpi.com

Coevolution of actions, personal norms, and beliefs about others in social dilemmas

Complexity Digest - Mon, 04/05/2021 - 14:03

Sergey Gavrilets

Human decision-making is affected by a diversity of factors including material cost-benefit considerations, normative and cultural influences, learning, and conformity with peers and external authorities (e.g., cultural, religious, political, organizational). Also important are their dynamically changing personal perception of the situation and beliefs about actions and expectations of others as well as psychological phenomena such as cognitive dissonance, and social projection. To better understand these processes, I develop a modeling framework describing the joint dynamics of actions and attitudes of individuals and their beliefs about actions and attitudes of their group-mates. I consider which norms get internalized and which factors control beliefs about others. I predict that the long-term average characteristics of groups are largely determined by a balance between material payoffs and the values promoted by the external authority. Variation around these averages largely reflects variation in individual costs and benefits mediated by individual psychological characteristics. The efforts of an external authority to change the group behavior in a certain direction can, counter-intuitively, have an opposite effect on individual behavior. I consider how various factors can affect differences between groups and societies in tightness/looseness of their social norms. I show that the most important factors are social heterogeneity, societal threat, effects of the authority, cultural variation in the degree of collectivism/individualism, the population size, and the subsistence style. My results can be useful for achieving a better understanding of human social behavior, historical and current social processes, and in developing more efficient policies aiming to modify social behavior

Read the full article at: osf.io

When will the COVID-19 pandemic end?

Complexity Digest - Sun, 03/28/2021 - 13:43

This article updates our perspectives on when the coronavirus pandemic will end to reflect the latest information on vaccine rollout, variants of concern, and disease progression. In the United Kingdom and the United States, we see progress toward a transition to normalcy during the second quarter of 2021. The new wave of cases in the European Union means that a similar transition is likely to come later there, in the late second or third quarter. Improved vaccine availability makes herd immunity most likely in the third quarter for the United Kingdom and the United States and in the fourth quarter for the European Union, but risks threaten that timeline. The timeline in other countries will depend on seven crucial variables. And when herd immunity is reached, the risks will not vanish; herd immunity may prove temporary or be limited to regions in a country.

Read the full article at: www.mckinsey.com

Modularity and dynamics on complex networks

Complexity Digest - Sun, 03/28/2021 - 12:02

Lambiotte, R & Schaub, M

Complex networks are typically not homogeneous, as they tend to display an array of structures at different scales. A feature that has attracted a lot of research is their modular organisation, i.e., networks may often be considered as being composed of certain building blocks, or modules. In this book, we discuss a number of ways in which this idea of modularity can be conceptualised, focusing specifically on the interplay between modular network structure and dynamics taking place on a network. We discuss, in particular, how modular structure and symmetries may impact on network dynamics and, vice versa, how observations of such dynamics may be used to infer the modular structure. We also revisit several other notions of modularity that have been proposed for complex networks and show how these can be related to and interpreted from the point of view of dynamical processes on networks. Several references and pointers for further discussion and future work should inform practitioners and researchers, and may motivate further studies in this area at the core of Network Science.

Download the book at: ora.ox.ac.uk

The Mathematics of How Connections Become Global

Complexity Digest - Sat, 03/27/2021 - 11:44

Percolation theory illuminates the behavior of many kinds of networks, from cell-phone connections to disease transmission.

Read the full article at: www.scientificamerican.com

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