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International Journal of Complexity in Education

Complexity Digest - Fri, 12/06/2019 - 13:41

The International Journal of Complexity in Education, IJCE, is a new forum which publishes articles that are concerned with the application of complexity theory and related models in the field of education. The journal invites empirical papers, as well as theoretical and methodological contributions, literature reviews and short research reports. We also welcome book reviews. In each of these instances, however, the linkage between complexity theory and education needs to be made explicit, and it should be clear how the contribution adds to existing

knowledge in that area. IJCE is a peer reviewed open source journal. There are no publication charges.

 

The inaugural issue is planned for April 2020.
To be considered for inclusion in this first issue, send full papers by December 31, 2019.

Source: ijce.mercy.edu

How to Decide: Simple Tools for Making Better Choices: Annie Duke

Complexity Digest - Thu, 12/05/2019 - 18:14

Through a blend of compelling exercises, illustrations, and stories, the bestselling author of Thinking in Bets will train you to combat your own biases, address your weaknesses, and help you become a better and more confident decision-maker.

 

What do you do when you’re faced with a big decision? If you’re like most people, you probably make a pro and con list, spend a lot of time obsessing about decisions that didn’t work out, get caught in analysis paralysis, endlessly seek other people’s opinions to find just that little bit of extra information that might make you sure, and finally go with your gut.

What if there was a better way to make quality decisions so you can think clearly, feel more confident, second-guess yourself less, and ultimately be more decisive and be more productive?

Making good decisions doesn’t have to be a series of endless guesswork. Rather, it’s a teachable skill that anyone can sharpen. In How to Decide, bestselling author Annie Duke and former professional poker player lays out a series of tools anyone can use to make better decisions. You’ll learn:

• To identify and dismantle hidden biases.
• To extract the highest quality feedback from those whose advice you seek.
• To more accurately identify the influence of luck in the outcome of your decisions.
• When to decide fast, when to decide slow, and when to decide in advance.
• To make decisions that more effectively help you to realize your goals and live your values.

Through practical exercises and engaging thought experiments, this book helps you analyze key decisions you’ve made in the past and troubleshoot those you’re making in the future. Whether you’re picking investments, evaluating a job offer, or trying to figure out your romantic life, this book is the key to happier outcomes and fewer regrets.

Source: www.amazon.com

Cybernetics for the Newtonian diehard

Complexity Digest - Thu, 12/05/2019 - 16:10

This is a quick tour through Ashby’s Introduction to Cybernetics. Leads to the Cybernetic paradigm.

Source: www.youtube.com

Guiding the Self-organization of Cyber-Physical Systems

Complexity Digest - Tue, 12/03/2019 - 18:57

Self-organization offers a promising approach for designing adaptive systems. Given the inherent complexity of most cyber-physical systems, adaptivity is desired, as predictability is limited. Here I summarize different concepts and approaches that can facilitate self-organization in cyber-physical systems, and thus be exploited for design. Then I mention real-world examples of systems where self-organization has managed to provide solutions that outperform classical approaches, in particular related to urban mobility. Finally, I identify when a centralized, distributed, or self-organizing control is more appropriate.

 

Guiding the Self-organization of Cyber-Physical Systems
Carlos Gershenson

Source: arxiv.org

Complex Networks 2019 Conference Proceedings

Complexity Digest - Tue, 12/03/2019 - 15:41

The International Conference on Complex Networks and their Applications aims at bringing together researchers from different scientific communities working on areas related to complex networks.

Source: www.complexnetworks.org

Escaping optimization traps: the role of cultural adaptation and cultural exaptation in facilitating open-ended cumulative dynamics

Complexity Digest - Tue, 12/03/2019 - 14:13

Explaining the origins of cumulative culture, and how it is maintained over long timescales, constitutes a challenge for theories of cultural evolution. Previous theoretical work has emphasized two fundamental causal processes: cultural adaptation (where technologies are refined towards a functional objective) and cultural exaptation (the repurposing of existing technologies towards a new functional goal). Yet, despite the prominence of cultural exaptation in theoretical explanations, this process is often absent from models and experiments of cumulative culture. Using an agent-based model, where agents attempt to solve problems in a high-dimensional problem space, the current paper investigates the relationship between cultural adaptation and cultural exaptation and produces three major findings. First, cultural dynamics often end up in optimization traps: here, the process of optimization causes the dynamics of change to cease, with populations entering a state of equilibrium. Second, escaping these optimization traps requires cultural dynamics to explore the problem space rapidly enough to create a moving target for optimization. This results in a positive feedback loop of open-ended growth in both the diversity and complexity of cultural solutions. Finally, the results helped delineate the roles played by social and asocial mechanisms: asocial mechanisms of innovation drive the emergence of cumulative culture and social mechanisms of within-group transmission help maintain these dynamics over long timescales.

 

Escaping optimization traps: the role of cultural adaptation and cultural exaptation in facilitating open-ended cumulative dynamics

James Winters
Palgrave Communications volume 5, Article number: 149 (2019)

Source: www.nature.com

Climate tipping points — too risky to bet against

Complexity Digest - Sun, 12/01/2019 - 23:26

Politicians, economists and even some natural scientists have tended to assume that tipping points in the Earth system — such as the loss of the Amazon rainforest or the West Antarctic ice sheet — are of low probability and little understood. Yet evidence is mounting that these events could be more likely than was thought, have high impacts and are interconnected across different biophysical systems, potentially committing the world to long-term irreversible changes.

Here we summarize evidence on the threat of exceeding tipping points, identify knowledge gaps and suggest how these should be plugged. We explore the effects of such large-scale changes, how quickly they might unfold and whether we still have any control over them.

In our view, the consideration of tipping points helps to define that we are in a climate emergency and strengthens this year’s chorus of calls for urgent climate action — from schoolchildren to scientists, cities and countries.

Source: www.nature.com

Introduction to Artificial Life for People who Like AI

Complexity Digest - Sat, 11/30/2019 - 23:14

Artificial Life, often shortened as ALife. What is your first thought when reading those words? A brand of T-shirts? A Greg Egan novel?

For me and hundreds of ALifers, ALife is the bottom-up scientific study of the fundamental principles of life. Just as Artificial Intelligence researchers ponder the nature of intelligence by trying to build intelligent systems from scratch, ALife researchers investigate the nature of “life” by trying to build living systems from scratch.

Source: thegradient.pub

Complex Systems Summer School 2020 | Santa Fe Institute

Complexity Digest - Fri, 11/29/2019 - 23:12

The SFI Complex Systems Summer School (CSSS) offers an intensive 4-week introduction to complex behavior in mathematical, physical, living, and social systems. Lectures are taught by the faculty of the Santa Fe Institute (SFI) and other leading educators and scholars. The school is for graduate students, postdoctoral fellows, and professionals seeking to transcend traditional disciplinary boundaries, take intellectual risks, and ask big questions about complex systems.

The program consists of an intensive series of lectures, labs, and discussions focusing on foundational concepts, tools, and current topics in complexity science. These include nonlinear dynamics, scaling theory, information theory, adaptation and evolution, networks, machine learning, agent-based models, and other topical areas and case studies. Participants collaborate in developing novel research projects throughout the four weeks of the program that culminate in final presentations and papers. 

 

June 14 – July 10, 2020

Source: santafe.edu

Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms

Complexity Digest - Thu, 11/28/2019 - 14:49

Complexity measures and information theory metrics in general have recently been attracting the interest of multi-agent and robotics communities, owing to their capability of capturing relevant features of robot behaviors, while abstracting from implementation details. We believe that theories and tools from complex systems science and information theory may be fruitfully applied in the near future to support the automatic design of robot swarms and the analysis of their dynamics. In this paper we discuss opportunities and open questions in this scenario.

 

Complexity Measures: Open Questions and Novel Opportunities in the Automatic Design and Analysis of Robot Swarms
Andrea Roli1, Antoine Ligot and Mauro Birattari

Front. Robot. AI, 26 November 2019

 

Source: www.frontiersin.org

Hidden complexity in Life-like rules

Complexity Digest - Thu, 11/28/2019 - 10:00

An alternative way to study the rules of life-like cellular automata is presented. The proposed perspective studies some multifractal and informational properties of Boolean functions behind these rules. Results from this approach challenge the traditional argument about the simplicity of Lifelike rules.

 

Hidden complexity in Life-like rules

Miguel Melgarejo, Marco Alzate, and Nelson Obregon
Phys. Rev. E 100, 052133

Source: journals.aps.org

The social physics collective

Complexity Digest - Sun, 11/24/2019 - 17:34

More than two centuries ago Henri de Saint-Simon envisaged physical laws to describe human societies. Driven by advances in statistical physics, network science, data analysis, and information technology, this vision is becoming a reality. Many of the grandest challenges of our time are of a societal nature, and methods of physics are increasingly playing a central role in improving our understanding of these challenges, and helping us to find innovative solutions. The Social physics Collection at Scientific Reports is dedicated to this research.

 

The social physics collective

Matjaž Perc
Scientific Reports volume 9, Article number: 16549 (2019)

Source: www.nature.com

Temporal Network Theory

Complexity Digest - Sun, 11/24/2019 - 14:01

This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena.

Network theory has proven, over the past 20 years to be one of the most powerful tools for the study and analysis of complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the "big data" sets. This monograph will appeal to students, researchers and professionals alike interested in theory and temporal networks, a field that has grown tremendously over the last decade.

 

Temporal Network Theory
Editors: Holme, Petter, Saramäki, Jari 

Source: www.springer.com

We Shouldn’t be Scared by ‘Superintelligent A.I.’

Complexity Digest - Fri, 11/22/2019 - 14:32

Intelligent machines catastrophically misinterpreting human desires is a frequent trope in science fiction, perhaps used most memorably in Isaac Asimov’s stories of robots that misconstrue the famous “three laws of robotics.” The idea of artificial intelligence going awry resonates with human fears about technology. But current discussions of superhuman A.I. are plagued by flawed intuitions about the nature of intelligence.

Source: www.nytimes.com

Reward and punishment in climate change dilemmas

Complexity Digest - Fri, 11/22/2019 - 13:56

Mitigating climate change effects involves strategic decisions by individuals that may choose to limit their emissions at a cost. Everyone shares the ensuing benefits and thereby individuals can free ride on the effort of others, which may lead to the tragedy of the commons. For this reason, climate action can be conveniently formulated in terms of Public Goods Dilemmas often assuming that a minimum collective effort is required to ensure any benefit, and that decision-making may be contingent on the risk associated with future losses. Here we investigate the impact of reward and punishment in this type of collective endeavors — coined as collective-risk dilemmas — by means of a dynamic, evolutionary approach. We show that rewards (positive incentives) are essential to initiate cooperation, mostly when the perception of risk is low. On the other hand, we find that sanctions (negative incentives) are instrumental to maintain cooperation. Altogether, our results are gratifying, given the a-priori limitations of effectively implementing sanctions in international agreements. Finally, we show that whenever collective action is most challenging to succeed, the best results are obtained when both rewards and sanctions are synergistically combined into a single policy.

 

Reward and punishment in climate change dilemmas
António R. Góis, Fernando P. Santos, Jorge M. Pacheco & Francisco C. Santos 
Scientific Reports volume 9, Article number: 16193 (2019)

Source: www.nature.com

César Hidalgo on Information in Societies, Economies, and the Universe

Complexity Digest - Fri, 11/22/2019 - 11:38

Maxwell’s Demon is a famous thought experiment in which a mischievous imp uses knowledge of the velocities of gas molecules in a box to decrease the entropy of the gas, which could then be used to do useful work such as pushing a piston. This is a classic example of converting information (what the gas molecules are doing) into work. But of course that kind of phenomenon is much more widespread — it happens any time a company or organization hires someone in order to take advantage of their know-how. César Hidalgo has become an expert in this relationship between information and work, both at the level of physics and how it bubbles up into economies and societies. Looking at the world through the lens of information brings new insights into how we learn things, how economies are structured, and how novel uses of data will transform how we live.

Source: www.preposterousuniverse.com

On Markov blankets and hierarchical self-organisation

Complexity Digest - Thu, 11/21/2019 - 16:26

Biological self-organisation can be regarded as a process of spontaneous pattern formation; namely, the emergence of structures that distinguish themselves from their environment. This process can occur at nested spatial scales: from the microscopic (e.g., the emergence of cells) to the macroscopic (e.g. the emergence of organisms). In this paper, we pursue the idea that Markov blankets – that separate the internal states of a structure from external states – can self-assemble at successively higher levels of organisation. Using simulations, based on the principle of variational free energy minimisation, we show that hierarchical self-organisation emerges when the microscopic elements of an ensemble have prior (e.g., genetic) beliefs that they participate in a macroscopic Markov blanket: i.e., they can only influence – or be influenced by – a subset of other elements. Furthermore, the emergent structures look very much like those found in nature (e.g., cells or organelles), when influences are mediated by short range signalling. These simulations are offered as a proof of concept that hierarchical self-organisation of Markov blankets (into Markov blankets) can explain the self-evidencing, autopoietic behaviour of biological systems.

 

On Markov blankets and hierarchical self-organisation
Ensor Rafael Palacios, Adeel Razi, Thomas Parr, Michael Kirchhoff, Karl Friston

Journal of Theoretical Biology

Source: www.sciencedirect.com

Generalizing RNA velocity to transient cell states through dynamical modeling

Complexity Digest - Thu, 11/21/2019 - 14:30

The introduction of RNA velocity in single cells has opened up new ways of studying cellular differentiation. The originally proposed framework obtains velocities as the deviation of the observed ratio of spliced and unspliced mRNA from an inferred steady state. Errors in velocity estimates arise if the central assumptions of a common splicing rate and the observation of the full splicing dynamics with steady-state mRNA levels are violated. With scVelo (https://scvelo.org), we address these restrictions by solving the full transcriptional dynamics of splicing kinetics using a likelihood-based dynamical model. This generalizes RNA velocity to a wide variety of systems comprising transient cell states, which are common in development and in response to perturbations. We infer gene-specific rates of transcription, splicing and degradation, and recover the latent time of the underlying cellular processes. This latent time represents the cell’s internal clock and is based only on its transcriptional dynamics. Moreover, scVelo allows us to identify regimes of regulatory changes such as stages of cell fate commitment and, therein, systematically detects putative driver genes. We demonstrate that scVelo enables disentangling heterogeneous subpopulation kinetics with unprecedented resolution in hippocampal dentate gyrus neurogenesis and pancreatic endocrinogenesis. We anticipate that scVelo will greatly facilitate the study of lineage decisions, gene regulation, and pathway activity identification.

 

Generalizing RNA velocity to transient cell states through dynamical modeling
Volker Bergen, Marius Lange, Stefan Peidli, F. Alexander Wolf, Fabian J. Theis

Source: www.biorxiv.org

Nonlinearity + Networks: A 2020 Vision

Complexity Digest - Thu, 11/21/2019 - 13:58

I briefly survey several fascinating topics in networks and nonlinearity. I highlight a few methods and ideas, including several of personal interest, that I anticipate to be especially important during the next several years. These topics include temporal networks (in which the entities and/or their interactions change in time), stochastic and deterministic dynamical processes on networks, adaptive networks (in which a dynamical process on a network is coupled to dynamics of network structure), and network structure and dynamics that include "higher-order" interactions (which involve three or more entities in a network). I draw examples from a variety of scenarios, including contagion dynamics, opinion models, waves, and coupled oscillators.

 

Nonlinearity + Networks: A 2020 Vision
Mason A. Porter

Source: arxiv.org

Is the World Chaos, a Machine, or Evolving Complexity? How Well Can We Understand Life and World Affairs?

Complexity Digest - Thu, 11/21/2019 - 10:23

Chaos, machine, or evolving complexity? The butterfly effect suggests a world in chaos—with linkages so random or nuanced that just to measure or pre-state them is virtually impossible. To predict how they will interact is even less feasible. Thanks to “adjacent possibles” and the contradictory impulses of human behavior, much of our world appears to move in random spasms. Every new technology and policy outcome creates opportunities to push society in new and often unforeseen directions, driven by human agents who may introduce crucial but unpredictable goals, strategies, and actions. Against this view, complexity science seeks to identify patterns in interactive relationships. Many patterns can be plotted and, in some cases, foreseen. A comparison of political entities across the globe points to certain factors conducing to societal fitness. Analysis of states that have declined in fitness suggests why their strengths turned to weaknesses. A survey of societies that were relatively democratic points to several factors that contributed to their acquiring authoritarian regimes. Scientists and scholars can unveil some elements of order but should strive to do so without hubris. Wise policymakers will strive to channel both the “actuals” and “adjacent possibles” that then arise toward constructive futures.

 

NETSOL: New Trends in Social and Liberal Sciences

Year: 2019 / Volume : 2 / Area: Interdisciplinary Studies

Walter C. Clemens and Stuart A. Kauffman
Is the World Chaos, a Machine, or Evolving Complexity? How Well Can We Understand Life and World Affairs? pp.24-43.

Source: www.netsoljournal.net

Pages

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