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AlphaFold: Using AI for scientific discovery | DeepMind

Complexity Digest - Fri, 01/24/2020 - 11:29

In our study published today in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and machine learning to apply cutting-edge techniques to predict the 3D structure of a protein based solely on its genetic sequence.

Source: deepmind.com

Universals and variations in moral decisions made in 42 countries by 70,000 participants

Complexity Digest - Thu, 01/23/2020 - 17:36

Edmond Awad, Sohan Dsouza, Azim Shariff, Iyad Rahwan, and Jean-François Bonnefon


We report the largest cross-cultural study of moral preferences in sacrificial dilemmas, that is, the circumstances under which people find it acceptable to sacrifice one life to save several. On the basis of 70,000 responses to three dilemmas, collected in 10 languages and 42 countries, we document a universal qualitative pattern of preferences together with substantial country-level variations in the strength of these preferences. In particular, we document a strong association between low relational mobility (where people are more cautious about not alienating their current social partners) and the tendency to reject sacrifices for the greater good—which may be explained by the positive social signal sent by such a rejection. We make our dataset publicly available for researchers.



Source: www.pnas.org

Complex economic activities concentrate in large cities

Complexity Digest - Wed, 01/22/2020 - 17:04

Pierre-Alexandre Balland, Cristian Jara-Figueroa, Sergio G. Petralia, Mathieu P. A. Steijn, David L. Rigby & César A. Hidalgo 
Nature Human Behaviour (2020)


Human activities, such as research, innovation and industry, concentrate disproportionately in large cities. The ten most innovative cities in the United States account for 23% of the national population, but for 48% of its patents and 33% of its gross domestic product. But why has human activity become increasingly concentrated? Here we use data on scientific papers, patents, employment and gross domestic product, for 353 metropolitan areas in the United States, to show that the spatial concentration of productive activities increases with their complexity. Complex economic activities, such as biotechnology, neurobiology and semiconductors, concentrate disproportionately in a few large cities compared to less–complex activities, such as apparel or paper manufacturing. We use multiple proxies to measure the complexity of activities, finding that complexity explains from 40% to 80% of the variance in urban concentration of occupations, industries, scientific fields and technologies. Using historical patent data, we show that the spatial concentration of cutting-edge technologies has increased since 1850, suggesting a reinforcing cycle between the increase in the complexity of activities and urbanization. These findings suggest that the growth of spatial inequality may be connected to the increasing complexity of the economy.

Source: www.nature.com

Reactive, Proactive, and Inductive Agents: An Evolutionary Path for Biological and Artificial Spiking Networks

Complexity Digest - Wed, 01/22/2020 - 15:41

Lana Sinapayen, Atsushi Masumori, and Takashi Ikegami

Front. Comput. Neurosci., 22 January 2020


Complex environments provide structured yet variable sensory inputs. To best exploit information from these environments, organisms must evolve the ability to anticipate consequences of new stimuli, and act on these predictions. We propose an evolutionary path for neural networks, leading an organism from reactive behavior to simple proactive behavior and from simple proactive behavior to induction-based behavior. Based on earlier in-vitro and in-silico experiments, we define the conditions necessary in a network with spike-timing dependent plasticity for the organism to go from reactive to proactive behavior. Our results support the existence of specific evolutionary steps and four conditions necessary for embodied neural networks to evolve predictive and inductive abilities from an initial reactive strategy.

Source: www.frontiersin.org

Analysis and control of epidemics in temporal networks with self-excitement and behavioral changes

Complexity Digest - Wed, 01/22/2020 - 14:29

Lorenzo Zino, Alessandro . Rizzo, Maurizio Porfiri

European Journal of Control


The complexity of interaction patterns among individuals in social systems plays a fundamental role on the inception and spreading of epidemic outbreaks. Empirical evidence has shown that the network of social interactions may co-evolve with the spread of the disease at comparable time-scales. Time-varying features have also been documented in the study of the propensity of individuals toward social activity, leading to the emergence of burstiness and temporal clustering. These temporal network dynamics are not independent of the disease evolution, whereby infected individuals could experience changes in their tendency to form connections, spontaneously or due to exogenous control policies. Neglecting these phenomena in modeling epidemics could lead to dangerous mispredictions of an outbreak and ineffective control interventions. In this paper, we propose a mathematically tractable modeling framework that relies on a limited number of parameters and encapsulates all these instances of complex phenomena through the lens of activity driven networks. Hawkes processes, Markov chains, and stability theory are leveraged to assist in the analysis of the framework and the formulation of theory-based control interventions. Our mathematical findings confirm the intuition that bursty activity patterns, typical of humans, facilitate epidemic spreading, while behavioral changes aiming at individual isolation could accelerate the eradication of epidemics. The proposed tools are demonstrated on a real-world case of influenza spreading in Italy. Overall, this work contributes new insight into the theory of temporal networks, laying the foundations for the analysis and control of spreading processes over networks with complex interaction patterns.

Source: www.sciencedirect.com

Neural Dendrites Reveal Their Computational Power

Complexity Digest - Tue, 01/21/2020 - 17:38

The dendritic arms of some human neurons can perform logic operations that once seemed to require whole neural networks.

Source: www.quantamagazine.org

Mediterranean School of Complex Networks 2020

Complexity Digest - Tue, 01/21/2020 - 16:59

Date: 5 Sep – 12 Sep 2020
Location: Salina, Sicily


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 Sixth Edition in 2019 of the Mediterranean School of Complex Networks, we call for applications to the Seventh Edition in 2020.

Source: mediterraneanschoolcomplex.net

Network experiment demonstrates converse symmetry breaking

Complexity Digest - Tue, 01/21/2020 - 10:23

F. Molnar, T. Nishikawa, and A.E. Motter,
Nature Physics (2020), doi:10.1038/s41567-019-0742-y.

Symmetry breaking—the phenomenon in which the symmetry of a system is not inherited by its stable states—underlies pattern formation, superconductivity and numerous other effects. Recent theoretical work has established the possibility of converse symmetry breaking, a phenomenon in which the stable states are symmetric only when the system itself is not. This includes scenarios in which interacting entities are required to be non-identical in order to exhibit identical behaviour, such as in reaching consensus. Here we present an experimental demonstration of this phenomenon. Using a network of alternating-current electromechanical oscillators, we show that their ability to achieve identical frequency synchronization is enhanced when the oscillators are tuned to be suitably non-identical and that converse symmetry breaking persists for a range of noise levels. These results have implications for the optimization and control of network dynamics in a broad class of systems whose function benefits from harnessing uniform behaviour.

Source: www.nature.com

A scalable pipeline for designing reconfigurable organisms

Complexity Digest - Sat, 01/18/2020 - 14:59

Sam Kriegman, Douglas Blackiston, Michael Levin, and Josh Bongard


Most technologies are made from steel, concrete, chemicals, and plastics, which degrade over time and can produce harmful ecological and health side effects. It would thus be useful to build technologies using self-renewing and biocompatible materials, of which the ideal candidates are living systems themselves. Thus, we here present a method that designs completely biological machines from the ground up: computers automatically design new machines in simulation, and the best designs are then built by combining together different biological tissues. This suggests others may use this approach to design a variety of living machines to safely deliver drugs inside the human body, help with environmental remediation, or further broaden our understanding of the diverse forms and functions life may adopt.

Source: www.pnas.org

Report: The future of urban science: integrating the social and natural sciences 

Complexity Digest - Fri, 01/17/2020 - 16:42

Urban science seeks to understand the fundamental processes that drive, shape and sustain cities and urbanization. It is a multi/transdisciplinary approach involving concepts, methods and research from the social, natural, engineering and computational sciences, along with the humanities. This report is intended to convey the current “state of the art” in urban science while also clearly indicating how urban science builds upon and complements (but does not replace) prior work on cities and urbanization in many other disciplines. The report does not aim at a fully comprehensive synopsis of work done under the rubric of “urban science” but it does aim to convey what makes urban science different from discipline-based examinations of cities and urbanization. It also highlights novel insights generated by the inherently multidisciplinary inquiry that urban science exemplifies."

Source: www.colorado.edu

Tenth International Conference on Complex Systems

Complexity Digest - Fri, 01/17/2020 - 13:43

The International Conference on Complex Systems is a unique interdisciplinary forum that unifies and bridges the traditional domains of science and a multitude of real world systems. Participants will contribute and be exposed to mind expanding concepts and methods from across the diverse field of complex systems science. The conference will be held July 26-31, 2020, in Nashua, NH, USA.

Source: necsi.edu

W. Brian Arthur (Part 1) on The History of Complexity Economics

Complexity Digest - Thu, 01/16/2020 - 10:40

From its beginnings as a discipline nearly 150 years ago, economics rested on assumptions that don’t hold up when studied in the present day. The notion that our economic systems are in equilibrium, that they’re made of actors making simple rational and self-interested decisions with perfect knowledge of society— these ideas prove about as useful in the Information Age as Newton’s laws of motion are to quantum physicists. A novel paradigm for economics, borrowing insights from ecology and evolutionary biology, started to emerge at SFI in the late 1980s — one that treats our markets and technologies as systems out of balance, serving metabolic forces, made of agents with imperfect information and acting on fundamental uncertainty. This new complexity economics uses new tools and data sets to shed light on puzzles standard economics couldn’t answer — like why the economy grows, how sudden and cascading crashes happen, why some companies and cities lock in permanent competitive advantages, and how technology evolves. And complexity economics offers insights back to biology, providing a new lens through which to understand the vastly intricate exchanges on which human life depends.
This week’s guest is W. Brian Arthur, External Professor at the Santa Fe Institute, Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford, and Visiting Researcher at Xerox PARC. In this first part of a two-episode conversation, we discuss the heady early days when complex systems science took on economics, and how biology provided a new paradigm for understanding our financial and technological systems. Tune in next week for part two…

Source: castbox.fm

Postdoctoral Fellows in The Center for Social and Biomedical Complexity Indiana University Bloomington, Luddy School of Informatics, Computing, and Engineering

Complexity Digest - Tue, 01/14/2020 - 15:40

The Center for Social and Biomedical Complexity (CSBC: https://csbc.sice.indiana.edu) at Indiana University Bloomington is accepting applications for one or more full-time non-tenure track postdoctoral fellows to conduct interdisciplinary research in Complex Networks and Systems applied to various social, ecological, biological, medicine and health problems. The expected start date for the appointments is February 2020. Candidates interested in conducting research in urban community-environment systems, or network science methods to analyze and visualize information relevant for epilepsy and other chronic diseases are encouraged to apply. The appointments are full-time for 12 months, with potential to be extended an additional year subject to funding and satisfactory performance. We offer a competitive salary with generous benefits. The postdocs will join a dynamic and interdisciplinary team that includes systems scientists, biologists, computer scientists, and social scientists. The postdocs will work with Prof. Luis M Rocha (https://informatics.indiana.edu/rocha/) and Prof. Johan Bollen (https://informatics.indiana.edu/jbollen/).

Source: chroniclevitae.com

ALIFE 2020

Complexity Digest - Tue, 01/14/2020 - 11:42

ALife is the flagship conference of the International Society for Artificial Life, which aims to bring together leading researchers and practitioners working on problems related to simulating and synthesizing complex phenomena in computation, biology, artificial intelligence, robotics, philosophy, and cognitive science, just to name a few. The ALife conference has a long history of encouraging multi-disciplinary collaboration across research, business, arts, and design and we look forward to upholding this long-standing tradition at the ALife 2020 conference. The conference theme for ALife 2020 is New Frontiers in AI: What can ALife offer AI?


  • Dates – July 13-18, 2020
  • Location – Centre Mont-Royal, Montréal, Québec, Canada
  • Hosts – University of Vermont, Vermont Complex Systems Center 
  • Twitter –  @ALifeConf

Source: www.vermontcomplexsystems.org

Decentralization in Digital Societies — A Design Paradox

Complexity Digest - Mon, 01/13/2020 - 15:29

Evangelos Pournaras


Digital societies come with a design paradox: On the one hand, technologies, such as Internet of Things, pervasive and ubiquitous systems, allow a distributed local intelligence in interconnected devices of our everyday life such as smart phones, smart thermostats, self-driving cars, etc. On the other hand, Big Data collection and storage is managed in a highly centralized fashion, resulting in privacy-intrusion, surveillance actions, discriminatory and segregation social phenomena. What is the difference between a distributed and a decentralized system design? How "decentralized" is the processing of our data nowadays? Does centralized design undermine autonomy? Can the level of decentralization in the implemented technologies influence ethical and social dimensions, such as social justice? Can decentralization convey sustainability? Are there parallelisms between the decentralization of digital technology and the decentralization of urban development?

Source: arxiv.org

Efficient sentinel surveillance strategies for preventing epidemics on networks

Complexity Digest - Mon, 01/13/2020 - 12:07

Ewan Colman, Petter Holme, Hiroki Sayama, Carlos Gershenson


Surveillance plays a crucial role in preventing emerging infectious diseases from becoming epidemic. In circumstances where it is possible to monitor the infection status of certain people, transport hubs, or hospitals, early detection of the disease allows interventions to be implemented before most of the damage can occur, or at least its impact can be mitigated. This paper addresses the question of which nodes we should select in a network of individuals susceptible to some infectious disease in order to minimize the number of casualties. By simulating disease outbreaks on a collection of empirical and synthetic networks we show that the best strategy depends on topological characteristics of the network. For highly modular or spatially embedded networks it is better to place the sentinels on nodes distributed across different regions. However, if the degree heterogeneity is high, then a strategy that targets network hubs is preferred. We further consider the consequences of having an incomplete sample of the network and demonstrate that the value of new information diminishes as more data is collected. Finally we find further marginal improvements using two heuristics informed by known results in graph theory that exploit the fragmented structure of sparse network data.

Source: journals.plos.org

Postdoctoral fellowships at UNAM

Complexity Digest - Mon, 01/13/2020 - 10:59

The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in September, 2020. Candidates should have obtained a PhD degree within the last five years to the date of the beginning of the fellowship.


The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy. Interested candidates should send CV and a tentative project/research interests (1 paragraph) to cgg-at-unam.mx by February 10th.

Source: complexes.blogspot.com

Postdoctoral fellowships at UNAM

Complexes - Mon, 01/13/2020 - 10:55
//Please forward to whom may be interested.
The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in September, 2020. Candidates should have obtained a PhD degree within the last five years to the date of the beginning of the fellowship.
The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy. Interested candidates should send CV and a tentative project/research interests (1 paragraph) to cgg-at-unam.mx by February 10th (we need some time for paperwork). 
Postdoctoral fellowships are between one and two years (after renewal). Spanish is not a requisite. Accepted candidates would be working at the Computer Science Department (http://turing.iimas.unam.mx ) of the IIMAS (http://www.iimas.unam.mx ), and/or at the Center for Complexity Sciences (http://c3.unam.mx/ ), both at UNAM's main campus. To know more about UNAM, visit http://turing.iimas.unam.mx/~cgg/unam.html
Requirements are available at https://dgapa.unam.mx/index.php/posdoctoral-2016 (check in the upper left corner for POSTDOCTORAL 2019 for documents from the previous call, only the dates have changed) . More information at https://dgapa.unam.mx/index.php/formacion-academica/posdoc [in Spanish].

There are two calls per year for these scholarships.


Complexity Digest - Sun, 01/12/2020 - 21:58

Network science is now a mature research field, whose growth was catalysed by the introduction of the ‘small world’ network model in 1998. Networks give mathematical descriptions of systems containing containing many interacting components, including power grids, neuronal networks and ecosystems. This collection brings together selected research, comments and review articles on how networks are structured (Layers & structure); how networks can describe healthy and disordered systems (Brain & disorders); how dynamics unfold on networks (Dynamics & spread); and community structures and resilience in networks (Community & resilience).

Source: www.nature.com

Active materials: minimal models of cognition?

Complexity Digest - Sun, 01/12/2020 - 13:56

Patrick McGivern

Adaptive Behavior


Work on minimal cognition raises a variety of questions concerning the boundaries of cognition. Many discussions of minimal cognition assume that the domain of minimal cognition is a subset of the domain of the living. In this article, I consider whether non-living ‘active materials’ ought to be included as instances of minimal cognition. I argue that seeing such cases as ‘minimal models’ of (minimal) cognition requires recognising them as members of a class of systems sharing the same basic features and exhibiting the same general patterns of behaviour. Minimal cognition in this sense is a very inclusive concept: rather than specifying some threshold level of cognition or a type of cognition found only in very simple systems, it is a concept of cognition associated with very minimal criteria that pick out only the most essential requirements for a system to exhibit cognitive behaviour.

Source: journals.sagepub.com


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