Feed aggregator

The economic impact of universities: Evidence from across the globe

Complexity Digest - Fri, 08/23/2019 - 08:16

•Using international data on universities we study their impact on regional growth.

•Increases in universities are positively and robustly associated with higher growth.

•This effect spills over into neighbouring regions within the same country.

•Increasing regional human capital and innovation matter help mediate this effect.

•The economic benefits of university expansion are likely to exceed the costs.


The economic impact of universities: Evidence from across the globe

Anna Valero, John Van Reenen

Economics of Education Review
Volume 68, February 2019, Pages 53-67

Source: www.sciencedirect.com

How to Defraud Democracy

Complexity Digest - Wed, 08/21/2019 - 14:40

  • There are still major cybersecurity vulnerabilities facing the 2020 U.S. presidential election, in part because the election system is based on faith instead of evidence.
  • Foreign attackers could target voter-registration rolls and election machinery to either influence the outcome or sow chaos and doubt.
  • The worst-case scenarios could result in an unprecedented constitutional crisis.

Source: www.scientificamerican.com

Settlement percolation: A study of building connectivity and poles of inaccessibility

Complexity Digest - Tue, 08/20/2019 - 07:51

•Spatial clustering is applied to coordinates of the building stock in Germany.

•We determine the percolation distance at which a country spanning cluster emerges.

•The top five largest holes in that mesh are or were military training areas.

•The building density decreases with the clustering threshold following a power-law with an exponent close to 0.75.

•The overbuilding is a phenomenon that is beyond the dichotomy of sprawled and compact urban development.


Settlement percolation: A study of building connectivity and poles of inaccessibility

Martin Behnisch, Martin Schorcht, Steffen Kriewald, DiegoRybski

Landscape and Urban Planning
Volume 191, November 2019, 103631

Source: www.sciencedirect.com

Sandy Pentland: The benefits of social physics – BBC Ideas

Complexity Digest - Mon, 08/19/2019 - 11:10

MIT’s Alex ‘Sandy’ Pentland explains ‘social physics’ – the analysis of human interactions to improve communities.

Source: www.bbc.com

Scientists must rise above politics — and restate their value to society

Complexity Digest - Sat, 08/17/2019 - 13:25

Scholars globally are feeling the heat from politicians. They should take inspiration from scientists in the 1950s who raised the alarm over nuclear weapons.

Source: www.nature.com

How Much Would You Pay to Change a Game before Playing It?

Complexity Digest - Fri, 08/16/2019 - 13:19

Envelope theorems provide a differential framework for determining how much a rational decision maker (DM) is willing to pay to alter the parameters of a strategic scenario. We generalize this framework to the case of a boundedly rational DM and arbitrary solution concepts. We focus on comparing and contrasting the case where DM’s decision to pay to change the parameters is observed by all other players against the case where DM’s decision is private information. We decompose DM’s willingness to pay a given amount into a sum of three factors: (1) the direct effect a parameter change would have on DM’s payoffs in the future strategic scenario, holding strategies of all players constant; (2) the effect due to DM changing its strategy as they react to a change in the game parameters, with the strategies of the other players in that scenario held constant; and (3) the effect there would be due to other players reacting to a the change in the game parameters (could they observe them), with the strategy of DM held constant. We illustrate these results with the quantal response equilibrium and the matching pennies game and discuss how the willingness to pay captures DM’s anticipation of their future irrationality.


How Much Would You Pay to Change a Game before Playing It?
David Wolpert and Justin Grana

Entropy 2019, 21(7), 686

Source: www.mdpi.com

Connecting empirical phenomena and theoretical models of biological coordination across scales

Complexity Digest - Wed, 08/14/2019 - 15:03

Coordination in living systems—from cells to people—must be understood at multiple levels of description. Analyses and modelling of empirically observed patterns of biological coordination often focus either on ensemble-level statistics in large-scale systems with many components, or on detailed dynamics in small-scale systems with few components. The two approaches have proceeded largely independent of each other. To bridge this gap between levels and scales, we have recently conducted a human experiment of mid-scale social coordination specifically designed to reveal coordination at multiple levels (ensemble, subgroups and dyads) simultaneously. Based on this experiment, the present work shows that, surprisingly, a single system of equations captures key observations at all relevant levels. It also connects empirically validated models of large- and small-scale biological coordination—the Kuramoto and extended Haken–Kelso–Bunz (HKB) models—and the hallmark phenomena that each is known to capture. For example, it exhibits both multistability and metastability observed in small-scale empirical research (via the second-order coupling and symmetry breaking in extended HKB) and the growth of biological complexity as a function of scale (via the scalability of the Kuramoto model). Only by incorporating both of these features simultaneously can we reproduce the essential coordination behaviour observed in our experiment.


Connecting empirical phenomena and theoretical models of biological coordination across scales
Mengsen Zhang , Christopher Beetle , J. A. Scott Kelso and Emmanuelle Tognoli

JRS Interface

Source: royalsocietypublishing.org

PHD/Postdoc Openings at Cross Labs

Complexity Digest - Wed, 08/14/2019 - 12:30

Cross Labs’ mission is to bridge between intelligence science and AI technology at the service of human society. At Cross Labs, we focus on pushing fundamental research towards a thorough mathematical understanding of all intelligent processes observable both in nature and in artificial environments.

To reach our goals, we are seeking ambitious, highly-skilled researchers to solve open problems on both natural and artificial intelligence fronts. Our current research priorities cover a large range of intelligence science topics, including artificial life, cognitive neuroscience, collective intelligence, deep learning, robotics, and computational linguistics. Other research topics will be seriously considered if you can make a case for their tractability and relevance to intelligence science research as envisioned by Cross Labs.

The ideal candidate shares our excitement to understand the fundamental principles of intelligence, has a career interest in our core research questions and aims to eventually develop into a senior research fellow at Cross Labs, or continue these avenues of research at another institution after completing substantial work at Cross Labs.

Source: www.crosslabs.org

Book review: Embodiment, enaction, and culture

Dr. Tom Froese - Tue, 08/13/2019 - 17:19

Here is my little book review of this big edited book on enactive approaches to culture!

Book Review: Embodiment, Enaction, and Culture: Investigating the Constitution of the Shared World

Tom Froese

This MIT Press volume edited by Durt et al. (2017) is concerned with investigating how people bring about a shared sociocultural world through participatory and broader collective sense-making processes, while at the same time highlighting how the participants in these social processes are themselves transformed by the world they help to bring forth. The key insight that runs through this interdisciplinary collection of 20 chapters is the irreducible nature of this interdependence between individual and collective processes: participation in, and hence the cultural reproduction of, patterned practices of the social world is only realizable via a thorough transformation of individual embodied minds.

Computational Human Dynamics

Complexity Digest - Sun, 08/11/2019 - 15:55

This thesis summarises my scientific contributions in the domain of network science, human dynamics and computational social science. These contributions are associated to computer science, physics, statistics, and applied mathematics. The goal of this thesis is twofold, on one hand to write a concise summary of my most interesting scientific contributions, and on the other hand to provide an up-to-date view and perspective about my field. I start my dissertation with an introduction to position the reader on the landscape of my field and to put in perspective my contributions. In the second chapter I concentrate on my works on bursty human dynamics, addressing heterogeneous temporal characters of human actions and interactions. Next, I discuss my contributions to the field of temporal networks and give a synthesises of my works on various methods of the representation, characterisation, and modelling of time-varying structures. Finally, I discuss my works on the data-driven observations and modelling of collective social phenomena. There, I summarise studies on the static observations of emergent patterns of socioeconomic inequalities and their correlations with social-communication networks, and with linguistic patterns. I also discuss dynamic observations and modelling of social contagion processes.


Computational Human Dynamics
Márton Karsai

Source: arxiv.org

Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters

Complexity Digest - Sun, 08/11/2019 - 12:49

Groups of firms often achieve a competitive advantage through the formation of geo-industrial clusters. Although many exemplary clusters are the subjects of case studies, systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale are scarce. In this work, we use LinkedIn’s employment history data from more than 500 million users over 25 years to construct a labor flow network of over 4 million firms across the world, from which we reveal hierarchical structure by applying network community detection. We show that the resulting geo-industrial clusters exhibit a stronger association between the influx of educated workers and financial performance, compared to traditional aggregation units. Furthermore, our analysis of the skills of educated workers reveals richer insights into the relationship between the labor flow of educated workers and productivity growth. We argue that geo-industrial clusters defined by labor flow provide useful insights into the growth of the economy.


Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters
Jaehyuk Park, Ian B. Wood, Elise Jing, Azadeh Nematzadeh, Souvik Ghosh, Michael D. Conover & Yong-Yeol Ahn
Nature Communications volume 10, Article number: 3449 (2019)

Source: www.nature.com

Hidden concepts in origins-of-life studies

Dr. Tom Froese - Sat, 08/10/2019 - 22:08

This review paper should be of interest for students looking for an overview of some of the less visible research currents in the study of origins of life:

Hidden concepts in the history and philosophy of origins-of-life studies: A workshop report

Carlos Mariscal, Ana Barahona, Nathanael Aubert-Kato, Arsev Umur Aydinoglu, Stuart Bartlett, María Luz Cárdenas, Kuhan Chandru, Carol Cleland, Benjamin T. Cocanougher, Nathaniel Comfort, Athel Cornish-Bowden, Terrence Deacon, Tom Froese, Donato Giovannelli, John Hernlund, Piet Hut, Jun Kimura, Marie-Christine Maurel, Nancy Merino, Alvaro Moreno, Mayuko Nakagawa, Juli Peretó, Nathaniel Virgo, Olaf Witkowski, and H. James Cleaves II

Fundamental Structures in Dynamic Communication Networks

Complexity Digest - Sat, 08/10/2019 - 12:50

In this paper I introduce a framework for modeling temporal communication networks and dynamical processes unfolding on such networks. The framework originates from the realization that there is a meaningful division of temporal communication networks into six dynamic classes, where the class of a network is determined by its generating process. In particular, each class is characterized by a fundamental structure: a temporal-topological network motif, which corresponds to the network representation of communication events in that class of network. These fundamental structures constrain network configurations: only certain configurations are possible within a dynamic class. In this way the framework presented here highlights strong constraints on network structures, which simplify analyses and shape network flows. Therefore the fundamental structures hold the potential to impact how we model temporal networks overall. I argue below that networks within the same class can be meaningfully compared, and modeled using similar techniques, but that integrating statistics across networks belonging to separate classes is not meaningful in general. This paper presents a framework for how to analyze networks in general, rather than a particular result of analyzing a particular dataset. I hope, however, that readers interested in modeling temporal networks will find the ideas and discussion useful in spite of the paper’s more conceptual nature.


Fundamental Structures in Dynamic Communication Networks
Sune Lehmann

Source: arxiv.org

Strategies and limitations in app usage and human mobility

Complexity Digest - Fri, 08/09/2019 - 12:45

Cognition has been found to constrain several aspects of human behaviour, such as the number of friends and the number of favourite places a person keeps stable over time. This limitation has been empirically defined in the physical and social spaces. But do people exhibit similar constraints in the digital space? We address this question through the analysis of pseudonymised mobility and mobile application (app) usage data of 400,000 individuals in a European country for six months. Despite the enormous heterogeneity of apps usage, we find that individuals exhibit a conserved capacity that limits the number of applications they regularly use. Moreover, we find that this capacity steadily decreases with age, as does the capacity in the physical space but with more complex dynamics. Even though people might have the same capacity, applications get added and removed over time. In this respect, we identify two profiles of individuals: app keepers and explorers, which differ in their stable (keepers) vs exploratory (explorers) behaviour regarding their use of mobile applications. Finally, we show that the capacity of applications predicts mobility capacity and vice-versa. By contrast, the behaviour of keepers and explorers may considerably vary across the two domains. Our empirical findings provide an intriguing picture linking human behaviour in the physical and digital worlds which bridges research studies from Computer Science, Social Physics and Computational Social Sciences.


Strategies and limitations in app usage and human mobility
Marco De Nadai, Angelo Cardoso, Antonio Lima, Bruno Lepri & Nuria Oliver 
Scientific Reportsvolume 9, Article number: 10935 (2019)

Source: www.nature.com

Optimal foraging and the information theory of gambling

Complexity Digest - Fri, 08/09/2019 - 06:49

At a macroscopic level, part of the ant colony life cycle is simple: a colony collects resources; these resources are converted into more ants, and these ants in turn collect more resources. Because more ants collect more resources, this is a multiplicative process, and the expected logarithm of the amount of resources determines how successful the colony will be in the long run. Over 60 years ago, Kelly showed, using information theoretic techniques, that the rate of growth of resources for such a situation is optimized by a strategy of betting in proportion to the probability of pay-off. Thus, in the case of ants, the fraction of the colony foraging at a given location should be proportional to the probability that resources will be found there, a result widely applied in the mathematics of gambling. This theoretical optimum leads to predictions as to which collective ant movement strategies might have evolved. Here, we show how colony-level optimal foraging behaviour can be achieved by mapping movement to Markov chain Monte Carlo (MCMC) methods, specifically Hamiltonian Monte Carlo (HMC). This can be done by the ants following a (noisy) local measurement of the (logarithm of) resource probability gradient (possibly supplemented with momentum, i.e. a propensity to move in the same direction). This maps the problem of foraging (via the information theory of gambling, stochastic dynamics and techniques employed within Bayesian statistics to efficiently sample from probability distributions) to simple models of ant foraging behaviour. This identification has broad applicability, facilitates the application of information theory approaches to understand movement ecology and unifies insights from existing biomechanical, cognitive, random and optimality movement paradigms. At the cost of requiring ants to obtain (noisy) resource gradient information, we show that this model is both efficient and matches a number of characteristics of real ant exploration.


Optimal foraging and the information theory of gambling
Roland J. Baddeley , Nigel R. Franks and Edmund R. Hunt

JRS Interface

Source: royalsocietypublishing.org

Data-driven strategies for optimal bicycle network growth

Complexity Digest - Thu, 08/08/2019 - 13:56

Urban transportation networks, from sidewalks and bicycle paths to streets and rail lines, provide the backbone for movement and socioeconomic life in cities. These networks can be understood as layers of a larger multiplex transport network. Because most cities are car-centric, the most developed layer is typically the street layer, while other layers can be highly disconnected. To make urban transport sustainable, cities are increasingly investing to develop their bicycle networks. However, given the usually patchy nature of the bicycle network layer, it is yet unclear how to extend it comprehensively and effectively given a limited budget. Here we develop data-driven, algorithmic network growth strategies and apply them to cities around the world, showing that small but focused investments allow to significantly increase the connectedness and directness of urban bicycle networks. We motivate the development of our algorithms with a network component analysis and with multimodal urban fingerprints that reveal different classes of cities depending on the connectedness between different network layers. We introduce two greedy algorithms to add the most critical missing links in the bicycle layer: The first algorithm connects the two largest connected components, the second algorithm connects the largest with the closest component. We show that these algorithms outmatch both a random approach and a baseline minimum investment strategy that connects the closest components ignoring size. Our computational approach outlines novel pathways from car-centric towards sustainable cities by taking advantage of urban data available on a city-wide scale. It is a first step towards a quantitative consolidation of bicycle infrastructure development that can become valuable for urban planners and stakeholders.


Data-driven strategies for optimal bicycle network growth
Luis Natera, Federico Battiston, Gerardo Iñiguez, Michael Szell

Source: arxiv.org

Modelling the Safety and Surveillance of the AI Race

Complexity Digest - Wed, 08/07/2019 - 07:52

Innovation, creativity, and competition are some of the fundamental underlying forces driving the advances in Artificial Intelligence (AI). This race for technological supremacy creates a complex ecology of choices that may lead to negative consequences, in particular, when ethical and safety procedures are underestimated or even ignored. Here we resort to a novel game theoretical framework to describe the ongoing AI bidding war, also allowing for the identification of procedures on how to influence this race to achieve desirable outcomes. By exploring the similarities between the ongoing competition in AI and evolutionary systems, we show that the timelines in which AI supremacy can be achieved play a crucial role for the evolution of safety prone behaviour and whether influencing procedures are required. When this supremacy can be achieved in a short term (near AI), the significant advantage gained from winning a race leads to the dominance of those who completely ignore the safety precautions to gain extra speed, rendering of the presence of reciprocal behavior irrelevant. On the other hand, when such a supremacy is a distant future, reciprocating on others’ safety behaviour provides in itself an efficient solution, even when monitoring of unsafe development is hard. Our results suggest under what conditions AI safety behaviour requires additional supporting procedures and provide a basic framework to model them.


Modelling the Safety and Surveillance of the AI Race
The Anh Han, Luis Moniz Pereira, Francisco C. Santos, Tom Lenaerts

Source: arxiv.org

Active inference: building a new bridge between control theory and embodied cognitive science

Complexity Digest - Sat, 08/03/2019 - 11:39

The application of Bayesian techniques to the study and computational modelling of biological systems is one of the most remarkable advances in the natural and cognitive sciences over the last 50 years. More recently, it has been proposed that Bayesian frameworks are not only useful for building descriptive models of biological functions, but that living systems themselves can be seen as Bayesian (inference) machines. On this view, the statistical tools more traditionally used to account for data in biology, neuroscience and psychology, are now used to model the mechanisms underlying functions and properties of living systems as if the systems themselves were the ones“calculating”those probabilities following Bayesian inference schemes. The free energy principle (FEP) is a framework proposed in light of this paradigm shift, advocating the minimisation of variational free energy, a proxy for sensory surprisal, as a general computational principle for biological systems. More intuitively and under some simplifying assumptions,the minimisation of variational free energy reduces,for an agent,to the minimisation of prediction errors on sensory input. Initially proposed as a candidate unifying theory of brain functioning, the FEP was later extended to encompass hypotheses on the origins of life, and is nowadays discussed in the cognitive science community for its possible implications for theories of the mind. In particular,one of the most popular process theories derived from the FEP,active inference,describes a biologically plausible algorithmic implementation of this principle with several repercussions on our understanding of cognition. In this thesis, I will focus on the role of this process theory for action and perception. In active inference, the two of them are combined in a closed sensorimotor loopasco-dependent processes of minimisation of a single loss function,variational free energy, with respect to different sets of variables. Building on this, I will suggest that some of the core ideas of active inference are best seen in terms of enactive, embodied, extended and embedded (4E) theories, in contrast to the majority of the literature emphasising its apparent connections to more traditional, computational, accounts of the mind. In particular, I will develop this argument by focusing on some proposals central to 4E approaches: (a) the non-brain-centric nature of cognitive processes,(b)the lack of explicit representations of the world,(c)the coupling of agent-environment systems and (d) the necessity of real-time feedback signals from the environment. Under the FEP formulation, I will present a series of case studies with mainly two objectives in mind: 1) to conceptually analyse and reframe these 4E ideas in the context of active inference, arguing for the advantages of their formalisation in a more general probabilistic (Bayesian) framework and, 2) to present new mathematical models and agent-based implementations of some of the conceptual connections between Bayesian inference frameworks and 4E proposals, largely missing in the literature.


Baltieri, Manuel (2019) Active inference: building a new bridge between control theory and embodied cognitive science. Doctoral thesis (PhD), University of Sussex.

Source: sro.sussex.ac.uk

Decoding the neuroscience of consciousness

Complexity Digest - Sat, 08/03/2019 - 09:37

A growing understanding of consciousness could lead to fresh treatments for brain injuries and phobias.

Source: www.nature.com

How to Make Change Happen

Complexity Digest - Sat, 08/03/2019 - 08:44

In this podcast, the author of Nudge, Professor Cass Sunstein, presents a guide for anyone who wishes to fuel – or block – transformative social change.

Sometimes all it takes to change society is for one person to decide they will no longer remain silent. A child announces that the emperor has no clothes. A woman tweets, #MeToo. Suddenly, a taboo collapses for the better – or for the worse. Once white nationalism was kept out of the mainstream media and politics; now it is in the White House. Social movements can begin when rage is released – or quietly, with millions of people nudged into making different decisions until, without noticing, we live with a new status quo.

Bringing together behavioural economics, psychology, politics and law, Cass Sunstein and LBC Presenter Matthew Stadlen explore Cass’s career new science of social movements. What can we as individuals do to harness the power of social movements to make change happen? What kinds of interventions make a difference, and what kind lead to bans and mandates? How can we overcome social division, cause transformative cascades, and employ political parties as a force for good?

Source: www.howtoacademy.com


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