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Bittorio revisited: structural coupling in the Game of Life

Complexity Digest - Tue, 07/30/2019 - 16:59

The notion of structural coupling plays a central role in Maturana and Varela’s biology of cognition framework and strongly influenced Varela’s subsequent enactive elaboration of this framework. Building upon previous work using a glider in the Game of Life (GoL) cellular automaton as a toy model of a minimal autopoietic system with which to concretely explore these theoretical frameworks, this article presents an analysis of structural coupling between a glider and its environment. Specifically, for sufficiently small GoL universes, we completely characterize the nonautonomous dynamics of both a glider and its environment in terms of interaction graphs, derive the set of possible glider lives determined by the mutual constraints between these interaction graphs, and show how such lives are embedded in the state transition graph of the entire GoL universe.


Bittorio revisited: structural coupling in the Game of Life
Randall D Beer

Adaptive Behavior

Source: journals.sagepub.com

Opening for Principal Investigator (Professor or Associate Professor) Earth-Life Science Institute, Tokyo Institute of Technology

Complexity Digest - Mon, 07/29/2019 - 16:46

ELSI aims to answer the fundamental questions of how the Earth was formed, how life originated in the environment of early Earth, and how this life evolved into complexity. ELSI pursues these questions by studying the "origin and evolution of life" and the "origin and evolution of the Earth" through an interdisciplinary collaboration between the fields of Earth, Life, and Planetary Sciences. By understanding the early Earth context that allowed for the rise of initial life, we also work to establish a greater understanding of the likelihood of extraterrestrial life elsewhere in the universe.
We are now seeking exceptional candidates for the role of Principal Investigator (Professor or Associate Professor) to lead world-class interdisciplinary research relevant to the origin and evolution of life. ELSI works positively to eliminate biases against gender or national origin. We welcome all qualified candidates, regardless of nationality or gender. We encourage and support our candidates’ close collaborations with overseas research institutes. Our institutional language is English; Japanese language skills are not required. An unprecedented level of support for researchers to live and thrive in Japan is provided by our talented staff.

Source: www.elsi.jp

ALIFE 2019: The 2019 Conference on Artificial Life

Complexity Digest - Sun, 07/28/2019 - 17:04

This volume presents the proceedings of ALife 2019, the 2019 Conference on Artificial Life. Open Access

Source: www.mitpressjournals.org

Who Is the Most Important Character in Frozen? What Networks Can Tell Us About the World

Complexity Digest - Sat, 07/27/2019 - 17:08

How do we determine the important characters in a movie like Frozen? We can watch it, of course, but there are also other ways—using mathematics and computers—to see who is important in the social network of a story. The idea is to compute numbers called centralities, which give ways of measuring who is important in networks. In this paper, we illustrate how different types of centralities measure importance in different ways. We also discuss how centralities are used to study many kinds of networks, not just social ones. In ongoing work, scientists are now developing centrality measures that also consider changes over time and different types of relationships.


Holme P, Porter M and Sayama H (2019) Who Is the Most Important Character in Frozen? What Networks Can Tell Us About the World. Front. Young Minds. 7:99. doi: 10.3389/frym.2019.00099

Source: kids.frontiersin.org

Predicting neighborhoods’ socioeconomic attributes using restaurant data

Complexity Digest - Fri, 07/26/2019 - 17:01

High-resolution socioeconomic data are crucial for place-based policy design and implementation, but it remains scarce for many developing cities and countries. We show that an easily accessible and timely updated neighborhood attribute, restaurant, when combined with machine-learning models, can be used to effectively predict a range of socioeconomic attributes. This approach allows us to collect training samples from representative neighborhoods and then use our trained model to infer unsampled neighborhoods in the city in a granular, timely, and low-cost manner. The good cross-city transferability performance of our model can also help bridge the “data gap” between cities, by training the model in cities with rich survey data and then applying it to cities where such data are unavailable.


Predicting neighborhoods’ socioeconomic attributes using restaurant data

Lei Dong, Carlo Ratti, and Siqi Zheng

Source: www.pnas.org

2019 Fall Program for Executives @NECSI

Complexity Digest - Thu, 07/25/2019 - 16:33

Organizations are operating in an increasingly complex global context.

Business and society are transforming and becoming increasingly complex. Artificial Intelligence, machine learning, big data analytics and hybrid human-machine systems are playing an increasing role in business products, strategy, and in the organization itself.

NECSI is hosting its two day Executive 2019 Fall Program in Washington, DC.

Source: necsi-exec.org

Curious About Consciousness? Ask the Self-Aware Machines

Complexity Digest - Thu, 07/25/2019 - 16:25

Consciousness is a famously hard problem, so Hod Lipson is starting from the basics: with self-aware robots that can help us understand how we think.

Source: www.quantamagazine.org

Estimating the success of re-identifications in incomplete datasets using generative models

Complexity Digest - Thu, 07/25/2019 - 07:41

While rich medical, behavioral, and socio-demographic data are key to modern data-driven research, their collection and use raise legitimate privacy concerns. Anonymizing datasets through de-identification and sampling before sharing them has been the main tool used to address those concerns. We here propose a generative copula-based method that can accurately estimate the likelihood of a specific person to be correctly re-identified, even in a heavily incomplete dataset. On 210 populations, our method obtains AUC scores for predicting individual uniqueness ranging from 0.84 to 0.97, with low false-discovery rate. Using our model, we find that 99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes. Our results suggest that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization set forth by GDPR and seriously challenge the technical and legal adequacy of the de-identification release-and-forget model.


Estimating the success of re-identifications in incomplete datasets using generative models
Luc Rocher, Julien M. Hendrickx & Yves-Alexandre de Montjoye
Nature Communicationsvolume 10, Article number: 3069 (2019)

Source: www.nature.com

Three papers in the ALIFE 2019 Proceedings

Dr. Tom Froese - Tue, 07/23/2019 - 16:00

This year’s artificial life conference (ALIFE 2019) will take place in Newcastle next week.

The conference proceedings have been published by MIT Press under an open access license.

Three of my graduate students will be presenting a part of their thesis research. Here are the titles of their contributions, with links to download the full papers:

From embodied interaction to compositional referential communication: A minimal agent-based model without dedicated communication channels

Jorge I. Campos and Tom Froese

Self-optimization in a Hopfield neural network based on the C. elegans connectome

Alejandro Morales and Tom Froese

Applying Social Network Analysis to Agent-Based Models: A Case Study of Task Allocation in Swarm Robotics Inspired by Ant Foraging Behavior

Georgina Montserrat Reséndiz-Benhumea, Tom Froese, Gabriel Ramos-Fernández, and Sandra E. Smith-Aguilar

Automatic Off-Line Design of Robot Swarms: A Manifesto

Complexity Digest - Tue, 07/23/2019 - 09:13

Designing collective behaviors for robot swarms is a difficult endeavor due to their fully distributed, highly redundant, and ever-changing nature. To overcome the challenge, a few approaches have been proposed, which can be classified as manual, semi-automatic, or automatic design. This paper is intended to be the manifesto of the automatic off-line design for robot swarms. We define the off-line design problem and illustrate it via a possible practical realization, highlight the core research questions, raise a number of issues regarding the existing literature that is relevant to the automatic off-line design, and provide guidelines that we deem necessary for a healthy development of the domain and for ensuring its relevance to potential real-world applications.


Automatic Off-Line Design of Robot Swarms: A Manifesto

Mauro Birattari, et al.

Front. Robot. AI, 19 July 2019

Source: www.frontiersin.org

Entropy | Special Issue : Thermodynamics and Information Theory of Living Systems

Complexity Digest - Tue, 07/23/2019 - 06:37

One of the defining features of living systems is their ability to process, exchange and store large amounts of information at multiple levels of organization, ranging from the biochemical to the ecological. At the same time, living entities are non-equilibrium—possibly at criticality—physical systems that continuously exchange matter and energy with structured environments, all while obeying the laws of thermodynamics. These properties not only lead to the emergence of biological information, but also impose constraints and trade-offs on the costs of such information processing. Some of these costs arise due to the particular properties of the material substrate of living matter in which information processing takes place, while others are universal and apply to all physical systems that process information.

In the past decade, the relationship between thermodynamics and information has received renewed scientific attention, attracting an increasing number of researchers and achieving significant progress. Despite this, the field is full of open problems and challenges at all levels, especially when dealing with biological systems. In spite of these difficulties, continued progress has the potential to fundamentally shape our future understanding of biology.

In this Special Issue we encourage researchers from theoretical biology, statistical physics, neuroscience, information theory, and complex systems to present their research on the connection between thermodynamics and information, with special emphasis on their implications for biological phenomena. We welcome contributions that focus on a particular biological system, as well as contributions that propose general theoretical approaches. We also welcome contributions that use mathematical techniques from statistical physics (variational methods, fluctuation theorems, uncertainty relations, etc.) to investigate biological questions.

Source: www.mdpi.com

Information Pollution by Social Bots

Complexity Digest - Mon, 07/22/2019 - 15:48

Social media are vulnerable to deceptive social bots, which can impersonate humans to amplify misinformation and manipulate opinions. Little is known about the large-scale consequences of such pollution operations. Here we introduce an agent-based model of information spreading with quality preference and limited individual attention to evaluate the impact of different strategies that bots can exploit to pollute the network and degrade the overall quality of the information ecosystem. We find that penetrating a critical fraction of the network is more important than generating attention-grabbing content and that targeting random users is more damaging than targeting hub nodes. The model is able to reproduce empirical patterns about exposure amplification and virality of low-quality information. We discuss insights provided by our analysis, with a focus on the development of countermeasures to increase the resilience of social media users to manipulation.


Information Pollution by Social Bots

Xiaodan Lou, Alessandro Flammini, Filippo Menczer

Source: arxiv.org

Complexity: Science, Engineering or a State of Mind? Towards a Scientific Renaissance

Complexity Digest - Sun, 07/14/2019 - 09:31

Is complexity a Science? Is it a possibly useful new way of engineering? In this video narrated by Maxi San Miguel it will be argued that Complexity is a new way of thinking necessary for a scientific renaissance that can transform society.

Source: www.youtube.com

Complexity in Medical Informatics

Complexity Digest - Fri, 07/12/2019 - 11:49

The topics of the accepted articles include but are not limited to the following: machine and deep learning approaches for health data; data mining and knowledge discovery in healthcare; clinical decision support systems; applications of the genetic algorithm in disease screening, diagnosis, and treatment planning; neurofuzzy system based on genetic algorithm for medical diagnosis and therapy support systems; applications of AI in healthcare; applications of artificial neural networks in medical science; electronic medical record and missing data; network and disease modeling (using administrative data); and health analytics and visualization.


Volume 2019, Article ID 8658124, 2 pages
Complexity in Medical Informatics
Panagiotis Vlamos, Ilias Kotsireas, and Dimitrios Vlachakis

Source: www.hindawi.com

Historical comparison of gender inequality in scientific careers across countries and disciplines

Complexity Digest - Fri, 07/12/2019 - 08:38

There is extensive, yet fragmented, evidence of gender differences in academia suggesting that women are under-represented in most scientific disciplines, publish fewer articles throughout a career, and their work acquires fewer citations. Here, we offer a comprehensive picture of longitudinal gender discrepancies in performance through a bibliometric analysis of academic careers by reconstructing the complete publication history of over 1.5 million gender-identified authors whose publishing career ended between 1955 and 2010, covering 83 countries and 13 disciplines. We find that, paradoxically, the increase of participation of women in science over the past 60 years was accompanied by an increase of gender differences in both productivity and impact. Most surprisingly though, we uncover two gender invariants, finding that men and women publish at a comparable annual rate and have equivalent career-wise impact for the same size body of work. Finally, we demonstrate that differences in dropout rates and career length explain a large portion of the reported career-wise differences in productivity and impact. This comprehensive picture of gender inequality in academia can help rephrase the conversation around the sustainability of women’s careers in academia, with important consequences for institutions and policy makers.


Historical comparison of gender inequality in scientific careers across countries and disciplines

Junming Huang, Alexander J. Gates, Roberta Sinatra, Albert-Laszlo Barabasi

Source: arxiv.org

Embodied robots driven by self-organized environmental feedback

Complexity Digest - Thu, 07/11/2019 - 19:11

Which kind of complex behavior may arise from self-organizing principles? We investigate this question for the case of snake-like robots composed of passively coupled segments, with every segment containing two wheels actuated separately by a single neuron. The robot is self-organized both on the level of the individual wheels and with respect to inter-wheel coordination, which arises exclusively from the mechanical coupling of the individual wheels and segments. For the individual wheel, the generating principle proposed results in locomotive states that correspond to self-organized limit cycles of the sensorimotor loop. Our robot interacts with the environment by monitoring the state of its actuators, that is, via propriosensation. External sensors are absent. In a structured environment the robot shows complex emergent behavior that includes pushing movable blocks around, reversing direction when hitting a wall, and turning when climbing a slope. On flat grounds the robot wiggles in a snake-like manner, when moving at higher velocities. We also investigate the emergence of motor primitives, namely, the route to locomotion, which is characterized by a series of local and global bifurcations in terms of dynamical system theory.


Embodied robots driven by self-organized environmental feedback
Frederike Kubandt, Michael Nowak, Tim Koglin, Claudius Gros, Bulcsú Sándor

Adaptive Behavior

Source: journals.sagepub.com

The Internet and your inner English tea merchant | Taha Yasseri | TEDxThessaloniki

Complexity Digest - Thu, 07/11/2019 - 09:39

The Internet is a totally internet phenomenon. In this talk, Dr Taha Yasseri gives answers to burning internet questions. Are users biased like an English tea merchant? Why do we care more about some events and not about others? And for how long do we care? He presents research findings on collective memory on the internet, as well as on the threshold of death toll that attracts our attention and empathy when it comes to social media. Although the interned is constantly criticized as being a threat to our democracy, he reminds us that it is a place of cooperation, a land that has the power to unite us, not divide us.

Source: www.youtube.com

Alternative Approaches to Economic Theory: Complexity, Post Keynesian and Ecological Economics. Edited By Victor A. Beker

Complexity Digest - Wed, 07/10/2019 - 11:52

The 2007–2008 financial crisis exposed the shortcomings of mainstream economic theory with economists unprepared to deal with it. In the face of this, a major rethinking of economics seems necessary and in presenting alternative approaches to economic theory, this book contributes to the rebuilding of the discipline.

This volume brings together contributions from different perspectives and theoretical approaches that address the challenge of updating the economic theory corpus and seek to recover prestige for this discipline after the failure of neoclassical economics. It addresses a range of topics, including the complexity approach to economics, category theory, the Post-Keynesian approach to micro and macroeconomics, financialisation, multidimensional analysis and ecological economics.

The book is aimed at economics scholars, researchers, academics and practitioners, as well as upper undergraduates and graduates in this area of knowledge. It may also be of interest for people interested in methodological issues in economics and the relationship between economic theory and the real world.


Alternative Approaches to Economic Theory:
Complexity, Post Keynesian and Ecological Economics
Edited By Victor A. Beker

Source: www.taylorfrancis.com

Element-centric clustering comparison unifies overlaps and hierarchy

Complexity Digest - Wed, 07/10/2019 - 09:54

Clustering is one of the most universal approaches for understanding complex data. A pivotal aspect of clustering analysis is quantitatively comparing clusterings; clustering comparison is the basis for many tasks such as clustering evaluation, consensus clustering, and tracking the temporal evolution of clusters. In particular, the extrinsic evaluation of clustering methods requires comparing the uncovered clusterings to planted clusterings or known metadata. Yet, as we demonstrate, existing clustering comparison measures have critical biases which undermine their usefulness, and no measure accommodates both overlapping and hierarchical clusterings. Here we unify the comparison of disjoint, overlapping, and hierarchically structured clusterings by proposing a new element-centric framework: elements are compared based on the relationships induced by the cluster structure, as opposed to the traditional cluster-centric philosophy. We demonstrate that, in contrast to standard clustering similarity measures, our framework does not suffer from critical biases and naturally provides unique insights into how the clusterings differ. We illustrate the strengths of our framework by revealing new insights into the organization of clusters in two applications: the improved classification of schizophrenia based on the overlapping and hierarchical community structure of fMRI brain networks, and the disentanglement of various social homophily factors in Facebook social networks. The universality of clustering suggests far-reaching impact of our framework throughout all areas of science.


Element-centric clustering comparison unifies overlaps and hierarchy
Alexander J. Gates, Ian B. Wood, William P. Hetrick & Yong-Yeol Ahn 
Scientific Reportsvolume 9, Article number: 8574 (2019)

Source: www.nature.com

A free energy principle for a particular physics

Complexity Digest - Wed, 07/10/2019 - 09:29

This monograph attempts a theory of every ‘thing’ that can be distinguished from other things in a statistical sense. The ensuing statistical independencies, mediated by Markov blankets, speak to a recursive composition of ensembles (of things) at increasingly higher spatiotemporal scales. This decomposition provides a description of small things; e.g., quantum mechanics – via the Schrodinger equation, ensembles of small things – via statistical mechanics and related fluctuation theorems, through to big things – via classical mechanics. These descriptions are complemented with a Bayesian mechanics for autonomous or active things. Although this work provides a formulation of every thing, its main contribution is to examine the implications of Markov blankets for self-organisation to nonequilibrium steady-state. In brief, we recover an information geometry and accompanying free energy principle that allows one to interpret the internal states of something as representing or making inferences about its external states. The ensuing Bayesian mechanics is compatible with quantum, statistical and classical mechanics and may offer a formal description of lifelike particles.


A free energy principle for a particular physics

Karl Friston

Source: arxiv.org


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