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2nd International School on Informatics and Dynamics in Complex Networks

Thu, 10/31/2019 - 06:28

The school is organized at the University of Catania, Italy, by the Department of Electrical Electronics and Computer Science and the Cometa Consortium, with the technical sponsorship of the Italian Society for Chaos and Complexity.
It consists of a series of lectures given by leading scientists in the field, aiming at providing a comprehensive treatment from background material to advanced results. The school is specially directed to PhD students and young researchers interested to the diverse aspects of the theory and applications of complex networks in science and engineering. The school aims at encouraging cross-disciplinary discussions between participants and speakers and start new joint researches.

 

2nd International School on Informatics and Dynamics in Complex Networks
University of Catania, Catania, Italy 10 -14 February 2020
Application Deadline: december 20th 2019

Source: isidcn.dieei.unict.it

Information Characteristics, Processes, and Mechanisms of Self-Organization Evolution

Wed, 10/30/2019 - 16:45

Self-organization is a general mechanism for the creation of new structural pattern of systems. A pattern, in essence, is a relationship, an architecture, a way of organizing, and a structure of order, which can only be explained by information activities. The characteristics of self-organization behavior, such as openness, nonlinearity, inner randomness, inner feedback, information network, and holographic construction, provide corresponding conditions and basis for the self-organizing evolution of the system from the aspects of environmental information function, maintenance and construction of the overall information framework of the system, and exploration of new information mode of the system. Based on the general process and mechanism of self-organization system evolution, its corresponding basic stages have the significance and value of information activities. Generally speaking, the process of system elements differentiating from the original system is the decoupling of information association between relevant elements and original systems. The convergence process of forming system elements is the initial exploration of forming a new information model; the nucleation process of some initial stabilization modes is the creation of information codons; the development of the system according to a particular pattern is ergodic construction of information feedback chain indicated by information codon; the diffusion of system self-replication is the expansion of the quantity of the information model; the variation in system self-replication is the innovation process of introducing new information pattern; environment-based selection and evolution correspond to the complex development of information pattern; and the alternation of old and new structures in system evolution corresponds to the formation process of the whole information network framework of the new system. In order to explain the self-organization’s characteristics, processes, and mechanisms of system evolution at a more comprehensive level, the complexity research program must pay enough attention to and give due status to the information factors and information science creed. Moreover, the information science research creed may also provide some basic theoretical paradigms with core theoretical significance for complex system research.

 

Information Characteristics, Processes, and Mechanisms of Self-Organization Evolution
Kun Wu and Qiong Nan

Complexity
Volume 2019, Article ID 5603685, 9 pages
https://doi.org/10.1155/2019/5603685

Source: www.hindawi.com

Sophisticated collective foraging with minimalist agents: a swarm robotics test

Mon, 10/28/2019 - 22:14

How groups of cooperative foragers can achieve efficient and robust collective foraging is of interest both to biologists studying social insects and engineers designing swarm robotics systems. Of particular interest are distance-quality trade-offs and swarm-size-dependent foraging strategies. Here, we present a collective foraging system based on virtual pheromones, tested in simulation and in swarms of up to 200 physical robots. Our individual agent controllers are highly simplified, as they are based on binary pheromone sensors. Despite being simple, our individual controllers are able to reproduce classical foraging experiments conducted with more capable real ants that sense pheromone concentration and follow its gradient. One key feature of our controllers is a control parameter which balances the trade-off between distance selectivity and quality selectivity of individual foragers. We construct an optimal foraging theory model that accounts for distance and quality of resources, as well as overcrowding, and predicts a swarm-size-dependent strategy. We test swarms implementing our controllers against our optimality model and find that, for moderate swarm sizes, they can be parameterised to approximate the optimal foraging strategy. This study demonstrates the sufficiency of simple individual agent rules to generate sophisticated collective foraging behaviour.

 

Sophisticated Collective Foraging with Minimalist Agents: A Swarm Robotics Test

M.S. Talamali, T. Bose, M. Haire, X. Xu, J.A.R. Marshall, A. Reina. Sophisticated Collective Foraging with Minimalist Agents: A Swarm Robotics Test. Swarm Intelligence 14(1):in press, 2020.
https://link.springer.com/article/10.1007/s11721-019-00176-9

Video: https://youtu.be/osQYuQ3cxmQ

Source: link.springer.com

Towards a quantitative model of epidemics during conflicts

Mon, 10/28/2019 - 15:47

Epidemics may contribute to and arise as a result of conflict. The effects of conflict on infectious diseases are complex. There have been counter-intuitive observations of both increase and decrease in disease outbreaks during and after conflicts. However there is no unified mathematical model that explains all these observations. There is an urgent need for a quantitative framework for modelling conflicts and epidemics. The article introduces a set of mathematical models to understand the role of conflicts in epidemics. The corresponding mathematical framework has the potential to explain the counter intuitive observations and the complex role of human conflicts in epidemics. This work suggests that aid and peacekeeping organizations should take an integrated approach that combines public health measures, socio-economic development, and peacekeeping in conflict zones.

This approach exemplifies the role of non-linear thinking in complex systems like human societies. The work presented should be looked upon as a first step towards a quantitative model of disease spread in conflicts.

 

Towards a quantitative model of epidemics during conflicts

Soumya Banerjee

INDECS

Source: indecs.eu

Success in books: predicting book sales before publication

Sat, 10/26/2019 - 09:44

Reading remains a preferred leisure activity fueling an exceptionally competitive publishing market: among more than three million books published each year, only a tiny fraction are read widely. It is largely unpredictable, however, which book will that be, and how many copies it will sell. Here we aim to unveil the features that affect the success of books by predicting a book’s sales prior to its publication. We do so by employing the Learning to Place machine learning approach, that can predicts sales for both fiction and nonfiction books as well as explaining the predictions by comparing and contrasting each book with similar ones. We analyze features contributing to the success of a book by feature importance analysis, finding that a strong driving factor of book sales across all genres is the publishing house. We also uncover differences between genres: for thrillers and mystery, the publishing history of an author (as measured by previous book sales) is highly important, while in literary fiction and religion, the author’s visibility plays a more central role. These observations provide insights into the driving forces behind success within the current publishing industry, as well as how individuals choose what books to read.

 

Success in books: predicting book sales before publication
Authors
Authors and affiliations
Xindi Wang, Burcu Yucesoy, Onur Varol, Tina Eliassi-Rad & Albert-László Barabási

EPJ Data Science
December 2019, 8:31

Source: link.springer.com

A Power Law Keeps the Brain’s Perceptions Balanced

Fri, 10/25/2019 - 20:49

Researchers have discovered a surprising mathematical relationship in the brain’s representations of sensory information, with possible applications to AI research.

Source: www.quantamagazine.org

Systematic comparison between methods for the detection of influential spreaders in complex networks

Fri, 10/25/2019 - 15:23

Influence maximization is the problem of finding the set of nodes of a network that maximizes the size of the outbreak of a spreading process occurring on the network. Solutions to this problem are important for strategic decisions in marketing and political campaigns. The typical setting consists in the identification of small sets of initial spreaders in very large networks. This setting makes the optimization problem computationally infeasible for standard greedy optimization algorithms that account simultaneously for information about network topology and spreading dynamics, leaving space only to heuristic methods based on the drastic approximation of relying on the geometry of the network alone. The literature on the subject is plenty of purely topological methods for the identification of influential spreaders in networks. However, it is unclear how far these methods are from being optimal. Here, we perform a systematic test of the performance of a multitude of heuristic methods for the identification of influential spreaders. We quantify the performance of the various methods on a corpus of 100 real-world networks; the corpus consists of networks small enough for the application of greedy optimization so that results from this algorithm are used as the baseline needed for the analysis of the performance of the other methods on the same corpus of networks. We find that relatively simple network metrics, such as adaptive degree or closeness centralities, are able to achieve performances very close to the baseline value, thus providing good support for the use of these metrics in large-scale problem settings. Also, we show that a further 2–5% improvement towards the baseline performance is achievable by hybrid algorithms that combine two or more topological metrics together. This final result is validated on a small collection of large graphs where greedy optimization is not applicable.

 

Systematic comparison between methods for the detection of influential spreaders in complex networks
Şirag Erkol, Claudio Castellano & Filippo Radicchi 
Scientific Reports volume 9, Article number: 15095 (2019)

Source: www.nature.com

Braess’s paradox and programmable behaviour in microfluidic networks

Fri, 10/25/2019 - 13:28

Microfluidic systems are now being designed with precision as miniaturized fluid manipulation devices that can execute increasingly complex tasks. However, their operation often requires numerous external control devices owing to the typically linear nature of microscale flows, which has hampered the development of integrated control mechanisms. Here we address this difficulty by designing microfluidic networks that exhibit a nonlinear relation between the applied pressure and the flow rate, which can be harnessed to switch the direction of internal flows solely by manipulating the input and/or output pressures. We show that these networks— implemented using rigid polymer channels carrying water—exhibit an experimentally supported fluid analogue of Braess’s paradox, in which closing an intermediate channel results in a higher, rather than lower, total flow rate. The harnessed behaviour is scalable and can be used to implement flow routing with multiple switches. These findings have the potential to advance the development of built-in control mechanisms in microfluidic networks, thereby facilitating the creation of portable systems and enabling novel applications in areas ranging from wearable healthcare technologies to deployable space systems.

 

Braess’s paradox and programmable behaviour in microfluidic networks
Daniel J. Case, Yifan Liu, István Z. Kiss, Jean-Régis Angilella & Adilson E. Motter 
Nature (2019)

Source: www.nature.com

Quantum computing takes flight

Fri, 10/25/2019 - 13:22

A programmable quantum computer has been reported to outperform the most powerful conventional computers in a specific task — a milestone in computing comparable in importance to the Wright brothers’ first flights.

Source: www.nature.com

Segregation and polarization in urban areas

Thu, 10/24/2019 - 12:55

Social behaviours emerge from the exchange of information among individuals—constrained by and reciprocally influencing the structure of information flows. The Internet radically transformed communication by democratizing broadcast capabilities and enabling easy and borderless formation of new acquaintances. However, actual information flows are heterogeneous and confined to self-organized echo-chambers. Of central importance to the future of society is understanding how existing physical segregation affects online social fragmentation. Here, we show that the virtual space is a reflection of the geographical space where physical interactions and proximity-based social learning are the main transmitters of ideas. We show that online interactions are segregated by income just as physical interactions are, and that physical separation reflects polarized behaviours beyond culture or politics. Our analysis is consistent with theoretical concepts suggesting polarization is associated with social exposure that reinforces within-group homogenization and between-group differentiation, and they together promote social fragmentation in mirrored physical and virtual spaces.

 

Segregation and polarization in urban areas
Alfredo J. Morales, Xiaowen Dong, Yaneer Bar-Yam and Alex ‘Sandy’ Pentland

Royal Society Open Science

Source: royalsocietypublishing.org

Probing complexity: thermodynamics and computational mechanics approaches to origins studies

Wed, 10/23/2019 - 13:35

This paper proposes new avenues for origins research that apply modern concepts from stochastic thermodynamics, information thermodynamics and complexity science. Most approaches to the emergence of life prioritize certain compounds, reaction pathways, environments or phenomena. What they all have in common is the objective of reaching a state that is recognizably alive, usually positing the need for an evolutionary process. As with life itself, this correlates with a growth in the complexity of the system over time. Complexity often takes the form of an intuition or a proxy for a phenomenon that defies complete understanding. However, recent progress in several theoretical fields allows the rigorous computation of complexity. We thus propose that measurement and control of the complexity and information content of origins-relevant systems can provide novel insights that are absent in other approaches. Since we have no guarantee that the earliest forms of life (or alien life) used the same materials and processes as extant life, an appeal to complexity and information processing provides a more objective and agnostic approach to the search for life’s beginnings. This paper gives an accessible overview of the three relevant branches of modern thermodynamics. These frameworks are not commonly applied in origins studies, but are ideally suited to the analysis of such non-equilibrium systems. We present proposals for the application of these concepts in both theoretical and experimental origins settings.

 

Probing complexity: thermodynamics and computational mechanics approaches to origins studies
Stuart J. Bartlett and Patrick Beckett

Interface Focus

Source: royalsocietypublishing.org

Large scale and information effects on cooperation in public good games

Wed, 10/23/2019 - 09:42

The problem of public good provision is central in economics and touches upon many challenging societal issues, ranging from climate change mitigation to vaccination schemes. However, results which are supposed to be applied to a societal scale have only been obtained with small groups of people, with a maximum group size of 100 being reported in the literature. This work takes this research to a new level by carrying out and analysing experiments on public good games with up to 1000 simultaneous players. The experiments are carried out via an online protocol involving daily decisions for extended periods. Our results show that within those limits, participants’ behaviour and collective outcomes in very large groups are qualitatively like those in smaller ones. On the other hand, large groups imply the difficulty of conveying information on others’ choices to the participants. We thus consider different information conditions and show that they have a drastic effect on subjects’ contributions. We also classify the individual decisions and find that they can be described by a moderate number of types. Our findings allow to extend the conclusions of smaller experiments to larger settings and are therefore a relevant step forward towards the understanding of human behaviour and the organisation of our society.

 

Large scale and information effects on cooperation in public good games
María Pereda, Ignacio Tamarit, Alberto Antonioni, Jose A. Cuesta, Penélope Hernández & Angel Sánchez
Scientific Reports volume 9, Article number: 15023 (2019)

Source: www.nature.com

Science and Technology Advance through Surprise

Tue, 10/22/2019 - 11:38

Breakthrough discoveries and inventions involve unexpected combinations of contents including problems, methods, and natural entities, and also diverse contexts such as journals, subfields, and conferences. Drawing on data from tens of millions of research papers, patents, and researchers, we construct models that predict more than 95% of next year’s content and context combinations with embeddings constructed from high-dimensional stochastic block models, where the improbability of new combinations itself predicts up to half of the likelihood that they will gain outsized citations and major awards. Most of these breakthroughs occur when problems in one field are unexpectedly solved by researchers from a distant other. These findings demonstrate the critical role of surprise in advance, and enable evaluation of scientific institutions ranging from education and peer review to awards in supporting it.

 

Science and Technology Advance through Surprise
Feng Shi, James Evans

Source: arxiv.org

Faculty Position in Statistical Physics of Complex Systems @EPFL

Tue, 10/22/2019 - 09:36

The School of Basic Sciences (Physics, Chemistry and Mathematics) at EPFL seeks to appoint a Professor in Statistical Physics of Complex Systems. This includes statistical physics of inference and learning, soft matter theory and theoretical biophysics. The appointment is offered at the Tenure Track Assistant Professor or tenured Associate Professor levels. We expect candidates to establish leadership and strengthen the EPFL endeavor in Statistical Physics of Complex Systems. Priority will be given to the overall originality and promise of the candidate’s work over any particular specialization area. Candidates should hold a PhD and have an excellent record of scientific accomplishments in the field. In addition, commitment to teaching at the undergraduate, master and doctoral levels is expected. Proficiency in French teaching is not required, but willingness to learn the language expected. EPFL, with its main campus located in Lausanne, Switzerland, on the shores of lake Geneva, is a dynamically growing and well-funded institution fostering excellence and diversity. It has a highly international campus with first-class infrastructure, including high performance computing As a technical university covering essentially the entire palette of engineering and science, EPFL offers a fertile environment for research cooperation between different disciplines. The EPFL environment is multi-lingual and multi-cultural, with English often serving as a common interface. Applications should include a cover letter, a CV with a list of publications, a concise statement of research (maximum 3 pages) and teaching interests (one page), and the names and addresses (including e-mail) of at least three references for a junior position or five references for a senior position. Applications should be uploaded (as PDFs) by November 15th, 2019 to https://facultyrecruiting.epfl.ch/position/18186240 Enquiries may be addressed to: Prof. Jan Hesthaven Dean of the School of Basic Sciences E-mail: fsbdean@epfl.ch Prof. Harald Brune Director of the Institute of Physics E-mail: IPHYSDirector@epfl.ch For additional information, please consult www.epfl.ch, sb.epfl.ch, iphys.epfl.ch EPFL is an equal opportunity employer and family friendly university. It is committed to increasing the diversity of its faculty. It strongly encourages women to Apply.

Source: www.epfl.ch

Melanie Mitchell’s ‘Artificial Intelligence’ exposes AI’s limits

Sun, 10/20/2019 - 15:53

Ever since its origin in post-war research, AI has been subject to profound hyperbole, rapturous prognostications, and projected nightmares. In 2019, things have once again reached fever pitch in what Science Board co-chair and External Professor Melanie Mitchell wryly notes is a hype cycle that routinely ripples through her fellow computer scientists and those who fund them. Her illuminating new book, Artificial Intelligence: A Guide for Thinking Humans, lays bare the inner workings of these potent tools, exposing their realistic limits and patiently detailing our deployment errors. It is a solid history of how we got from pocket calculators to facial recognition and self-driving cars, a lucid tour of how these systems operate, and a tempered read on just how far we have to go before we’re obsolete.

Source: www.santafe.edu

Pantheon

Fri, 10/18/2019 - 16:01

Pantheon is an observatory of human collective memory. With data on more than 70,000 biographies, Pantheon helps you explore the geography and dynamics of the most memorable people in our planet’s history.

Source: pantheon.world

Complex Networks: Theory, Methods, and Applications – Lake Como School of Advanced Studies – May 18-21, 2020

Wed, 10/16/2019 - 22:13

Many real systems can be modeled as networks, where the elements of the system are nodes and interactions between elements are edges. An even larger set of systems can be modeled using dynamical processes on networks, which are in turn affected by the dynamics. Networks thus represent the backbone of many complex systems, and their theoretical and computational analysis makes it possible to gain insights into numerous applications. Networks permeate almost every conceivable discipline—including sociology, transportation, economics and finance, biology, and myriad others—and the study of "network science" has thus become a crucial component of modern scientific education.

The school "Complex Networks: Theory, Methods, and Applications" offers a succinct education in network science. It is open to all aspiring scholars in any area of science or engineering who wish to study networks of any kind (whether theoretical or applied), and it is especially addressed to doctoral students and young postdoctoral scholars. The aim of the school is to deepen into both theoretical developments and applications in targeted fields.

LECTURERS
— REKA ALBERT, Pennsylvania State University
— GUIDO CALDARELLI, IMT Lucca
— MARTON KARSAI, Central European University
— JOSE FERNANDO MENDES, University of Aveiro
— NATASA PRZULJ, Barcelona Supercomputing Center

 

Spring School
COMPLEX NETWORKS: THEORY, METHODS, AND APPLICATIONS
(6th edition)

Lake Como School of Advanced Studies
Villa del Grumello, Como, Italy, 18-21 May 2020

Source: ntmf.lakecomoschool.org

11th International Conference on Complex Networks

Tue, 10/15/2019 - 10:17

 The International Conference on Complex Networks (CompleNet) brings together researchers and practitioners from diverse disciplines working on areas related to complex networks. In its 11th year, we are delighted to have the next CompleNet in Exeter UK hosted by the University of Exeter.

​Over the past two decades we have witnessed an exponential increase in the number of publications and research centers dedicated to this field. From biological systems to computer science, from technical to informational networks, from economic to social systems, complex networks are becoming pervasive for dozens of applications. It is the interdisciplinary nature of complex networks that CompleNet aims to capture and celebrate.

 

11th International Conference on Complex Networks
COMPLENET 2020
​31 March-3 April 2020
EXETER, UK

Source: complenet.weebly.com

The Prize in Economic Sciences 2019

Mon, 10/14/2019 - 08:44

The research conducted by this year’s Laureates has considerably improved our ability to fight global poverty. In just two decades, their new experiment-based approach has transformed development economics, which is now a flourishing field of research.

Despite recent dramatic improvements, one of humanity’s most urgent issues is the reduction of global poverty, in all its forms. More than 700 million people still subsist on extremely low incomes. Every year, around five million children under the age of five still die of diseases that could often have been prevented or cured with inexpensive treatments. Half of the world’s children still leave school without basic literacy and numeracy skills.

This year’s Laureates have introduced a new approach to obtaining reliable answers about the best ways to fight global poverty. In brief, it involves dividing this issue into smaller, more manageable, questions – for example, the most effective interventions for improving educational outcomes or child health. They have shown that these smaller, more precise, questions are often best answered via carefully designed experiments among the people who are most affected.

Source: www.nobelprize.org

Irreversibility and emergent structure in active matter

Thu, 10/10/2019 - 09:30

Active matter is rapidly becoming a key paradigm of out-of-equilibrium soft matter exhibiting complex collective phenomena, yet the thermodynamics of such systems remain poorly understood. In this article we study the dynamical irreversibility of large scale active systems capable of motility-induced phase separation and polar alignment. We use a model with momenta in both translational and rotational degrees of freedom, revealing a hidden component not previously reported in the literature. Steady state irreversibility is quantified at each point in the phase diagram which exhibits sharp discontinuities at phase transitions. Identification of the irreversibility in individual particles lays the groundwork for discussion of the thermodynamics of micro-features, such as defects in the emergent structure. The interpretation of the time reversal symmetry in the dynamics of the particles is found to be crucial.

 

Irreversibility and emergent structure in active matter
Phys. Rev. E
Emanuele Crosato, Mikhail Prokopenko, and Richard E. Spinney

Source: journals.aps.org

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