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Forecast: What Physics, Meteorology, and the Natural Sciences Can Teach Us About Economics (by Mark Buchanan)

Forecast: What Physics, Meteorology, and the Natural Sciences Can Teach Us About Economics

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In this deeply researched and piercingly intelligent book, physicist Mark Buchanan shows how a simple feedback loop can lead to major consequences, the kind predictable by mathematical models but hard for most people to anticipate. From his unique perspective, Buchanan argues that our basic assumptions about economic markets--that they are for the most part stable, with occasional interruptions--are simply wrong. Markets really act more like the weather: a brief heat wave can become a massive storm in a matter of a few days, or even hours.

The Physics of Finance reimagines the basics of how economics, with consequences that affect everyone.

 

 


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The future cities agenda

Suddenly, ‘cities’ have become the hottest topic on the planet. National research institutes and local governments as well as various global agencies are all scrambling to get a piece of the action as cities become the places where it is considered future economic prosperity firmly lies while also offering the prospect of rescuing a developed world mired in recession.

 

Batty M, 2013, "The future cities agenda" Environment and Planning B: Planning and Design 40(2) 191 – 194 

http://dx.doi.org/10.1068/b4002ed


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Evolutionary games on multilayer networks: A colloquium

Networks form the backbone of many complex systems, ranging from the Internet to human societies. Accordingly, not only is the range of our interactions limited and thus best described and modeled by networks, it is also a fact that the networks that are an integral part of such models are often interdependent or even interconnected. Networks of networks or multilayer networks are therefore a more apt description of social systems. This colloquium is devoted to evolutionary games on multilayer networks, and in particular to the evolution of cooperation as one of the main pillars of modern human societies. We first give an overview of the most significant conceptual differences between single-layer and multilayer networks, and we provide basic definitions and a classification of the most commonly used terms. Subsequently, we review fascinating and counterintuitive evolutionary outcomes that emerge due to different types of interdependencies between otherwise independent populations. The focus is on coupling through the utilities of players, through the flow of information, as well as through the popularity of different strategies on different network layers. The colloquium highlights the importance of pattern formation and collective behavior for the promotion of cooperation under adverse conditions, as well as the synergies between network science and evolutionary game theory.

 

Evolutionary games on multilayer networks: A colloquium
Zhen Wang, Lin Wang, Attila Szolnoki, Matjaz Perc

http://arxiv.org/abs/1504.04359


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Nonlinear Dynamics of Financial Crises: How to Predict Discontinuous Decisions (by Ionut Purica)

When just a handful of economists predicted the 2008 financial crisis, people should wonder how so many well educated people with enormous datasets and computing power can be so wrong. In this short book Ionut Purica joins a growing number of economists who explore the failings of mainstream economics and propose solutions developed in other disciplines, such as sociology and evolutionary biology. While it might be premature to call for a revolution, Dr. Purica echoes John Maynard Keynes in believing that economic ideas are "dangerous for good or evil." In recent years evil seems to have had the upper hand. "Nonlinear Dynamics of Financial Crises" points to their ability to do good.

Makes complex economics ideas accessible by carefully explaining technical terms and minimizing mathematics and equationsDelivers easily-understood perspectives about the global economy by constructing broad assumptions and conclusions in the face of its infinitely complexityChallenges received economic ideas by focusing on human behavior and the roles it plays in easily-observable recent trends and events

 

 


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Structural Determinants of Criticality in Biological Networks

Many adaptive evolutionary systems display spatial and temporal features, such as long-range correlations, typically associated with the critical point of a phase transition in statistical physics. Empirical and theoretical studies suggest that operating near criticality enhances the functionality of biological networks, such as brain and gene networks, in terms for instance of information processing, robustness and evolvability. While previous studies have explained criticality with specific system features, we still lack a general theory of critical behaviour in biological systems. Here we look at this problem from the complex systems perspective, since in principle all critical biological circuits have in common the fact that their internal organisation can be described as a complex network. An important question is how self-similar structure influences self-similar dynamics. Modularity and heterogeneity, for instance, affect the location of critical points and can be used to tune the system towards criticality. We review and discuss recent studies on the criticality of neuronal and genetic networks, and discuss the implications of network theory when assessing the evolutionary features of criticality.

 

Valverde S, Ohse S, Turalska M, Garcia-Ojalvo J and West BJ (2015). Structural Determinants of Criticality in Biological Networks. Front. Physiol. 6:127. http://dx.doi.org/10.3389/fphys.2015.00127 ;


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Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

 

Dong X, Bollen J (2015) Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics. PLoS ONE 10(3): e0120039. http://dx.doi.org/10.1371/journal.pone.0120039 ;


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Responding to Complexity in Socio-­Economic Systems: How to Build a Smart and Resilient Society?

The world is changing at an ever-increasing pace. And it has changed in a much more fundamental way than one would think, primarily because it has become more connected and interdependent than in our entire history. Every new product, every new invention can be combined with those that existed before, thereby creating an explosion of complexity: structural complexity, dynamic complexity, functional complexity, and algorithmic complexity. How to respond to this challenge?

 

Responding to Complexity in Socio-­Economic Systems: How to Build a Smart and Resilient Society?

Dirk Helbing

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2583391


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Requisite Variety, Autopoiesis, and Self-organization

Ashby's law of requisite variety states that a controller must have at least as much variety (complexity) as the controlled. Maturana and Varela proposed autopoiesis (self-production) to define living systems. Living systems also require to fulfill the law of requisite variety. A measure of autopoiesis has been proposed as the ratio between the complexity of a system and the complexity of its environment. Self-organization can be used as a concept to guide the design of systems towards higher values of autopoiesis, with the potential of making technology more "living", i.e. adaptive and robust.

 

Requisite Variety, Autopoiesis, and Self-organization
Carlos Gershenson

http://arxiv.org/abs/1409.7475


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Constructing a Continuous Futures Series From Quandl

Constructing a Continuous Futures Series From Quandl | Edgar Analytics & Complex Systems | Scoop.it
(This article was first published on Revolutions, and kindly contributed to R-bloggers)
by Ilya Kipnis
In this post, I will demonstrate how to obtain, stitch together, and clean data for backtesting using futures data from Quandl.

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Coevolution can reverse predator–prey cycles

The abundances of predators and their prey can oscillate in time. Mathematical theory of predator–prey systems predicts that in predator–prey cycles, peaks in prey abundance precede peaks in predator abundance. However, these models do not consider how the evolution of predator and prey traits related to offense and defense will affect the ordering and timing of peaks. Here we show that predator–prey coevolution can effectively reverse the ordering of peaks in predator–prey cycles, i.e., peaks in predator abundance precede peaks in prey abundance. We present examples from three distinct systems that exhibit reversed cycles, suggesting that coevolution may be an important driver of cycles in those systems.

 

http://dx.doi.org/10.1073/pnas.1317693111
Coevolution can reverse predator–prey cycles

Michael H. Cortez and Joshua S. Weitz

PNAS vol. 111 no. 20, pp. 7486–7491





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Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism

Guided self-organization can be regarded as a paradigm proposed to understand how to guide a self-organizing system towards desirable behaviors, while maintaining its non-deterministic dynamics with emergent features. It is, however, not a trivial problem to guide the self-organizing behavior of physically embodied systems like robots, as the behavioral dynamics are results of interactions among their controller, mechanical dynamics of the body, and the environment. This paper presents a guided self-organization approach for dynamic robots based on a coupling between the system mechanical dynamics with an internal control structure known as the attractor selection mechanism. The mechanism enables the robot to gracefully shift between random and deterministic behaviors, represented by a number of attractors, depending on internally generated stochastic perturbation and sensory input. The robot used in this paper is a simulated curved beam hopping robot: a system with a variety of mechanical dynamics which depends on its actuation frequencies. Despite the simplicity of the approach, it will be shown how the approach regulates the probability of the robot to reach a goal through the interplay among the sensory input, the level of inherent stochastic perturbation, i.e., noise, and the mechanical dynamics.

 

Guided Self-Organization in a Dynamic Embodied System Based on Attractor Selection Mechanism
Surya G. Nurzaman , Xiaoxiang Yu, Yongjae Kim and Fumiya Iida

Entropy 2014, 16(5), 2592-2610

http://www.mdpi.com/1099-4300/16/5/2592


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Eli Levine's curator insight, May 14, 2014 8:18 AM

This ties in with the concept of changing the software that runs on society's particular hardware.  Government is the control mechanism in a given society and it must obey the natural laws of the society in order to get the responses and effects that its members wish to have on the society.  This is similar to an airplane, in that the only way to get an airplane safely, reliably and consistently off the ground is to obey the natural laws of physics in the world that the airplane is also apart of.

 

It should be noted here that only benevolence, care, honesty, cost effectiveness and genuine action for the sake of the general public, however those are done, are the only ways for a government and its members to stay in power.  Underhanded techniques or the imposition of brute force will not work, especially in the context of an American society.  Such is how things work in our world.  And it's unfortunate that so many people who actually are holding political power in our society are so apparently clueless and unwilling to accept these principles in their daily courses of action.

 

Think about it.

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▶ Jeffrey Johnson: From networks to hypernetworks in complex systems science

Complex systems have multilevel dynamics emerging from interactions between their parts. Networks have provided deep insights into those dynamics, but only represent relations between two things while the generality is relations between many things. Hypergraphs and their related Galois connections have long been used to model such relations, but their set theoretic nature has inadequate and inappropriate structure. Simplicial complexes can better represent relations between many things but they too have limitations. Hypersimplices, which are defined as simplices in which the relational structure is explicit, overcome these limitations. Hypernetworks, which in the simplest cases are sets of hypersimplices, have a multidimensional connectivity structure which constrains those dynamics represented by patterns of numbers over the hypersimplices and their vertices. The dynamics of hypernetwork also involve the formation and disintegration of hypersimplices, which are seen as structural events related to system time. Hypernetworks provide algebraic structure able to represent multilevel systems and combine their top-down and bottom-up micro, meso and macro-dynamics. Hypernetworks naturally generalise graphs, hypergraphs and networks. These ideas will be presented in a graphical way through examples which also show the relevance of hypernetworks to policy. It will be argued that hypernetworks are necessary if not sufficient for a science of complex systems and its applications. The talk will be aimed at a general audience and no prior knowledge will be assumed.

 

10th ECCO / GBI seminar series. Spring 2014

From networks to hypernetworks in complex systems science

April 18, 2014, Brussels

Jeffrey Johnson Open University, UK

Slides, references and more: http://ecco.vub.ac.be/?q=node/231 


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Liz Rykert's curator insight, May 10, 2014 9:32 PM

I am fascinated with the role of networks in complex systems as the scaffolds that connect and conduct.  

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Chaos Theory in Politics (by Santo Banerjee et al.)

Chaos Theory in Politics (Understanding Complex Systems)

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The present work investigates global politics and political implications of social science and management with the aid of the latest complexity and chaos theories. Until now, deterministic chaos and nonlinear analysis have not been a focal point in this area of research. This book remedies this deficiency by utilizing these methods in the analysis of the subject matter. The authors provide the reader a detailed analysis on politics and its associated applications with the help of chaos theory, in a single edited volume.


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Unconventional Computation & Natural Computation 2014

The International Conference on Unconventional Computation and Natural Computation has been a forum where scientists with different backgrounds, yet sharing a common interest in novel forms of computation, human-designed computation inspired by nature, and the computational aspects of processes taking place in nature, meet and present their latest results.

 

Unconventional Computation & Natural Computation 2014
University of Western Ontario, London, Ontario, Canada, July 14-18

http://conferences.csd.uwo.ca/ucnc2014/


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Ants Swarm Like Brains Think

Ants Swarm Like Brains Think | Edgar Analytics & Complex Systems | Scoop.it
“As I watched films of these ant colonies, it looked like what was happening at the synapse of neurons. Both of these systems accumulate evidence about their inputs—returning ants or incoming voltage pulses—to make their decisions about whether to generate an output—an outgoing forager or a packet of neurotransmitter,” Goldman said. On his next trip to Stanford, he extended his stay. An unusual research collaboration had begun to coalesce: Ants would be used to study the brain, and the brain, to study ants.

 

http://nautil.us/issue/23/dominoes/ants-swarm-like-brains-think-rp


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Ingenious: David Krakauer

Ingenious: David Krakauer | Edgar Analytics & Complex Systems | Scoop.it

So one way of thinking about complexity is adaptive, many body systems. The sun is not an adaptive system; the sun doesn’t really learn. These do; these are learning systems. And we’ve never really successfully had a theory for many body learning systems. So just to make that a little clearer, the brain would be an example. There are many neurons interacting adaptively to form a representation, for example, of a visual scene; in economy, there are many individual agents deciding on the price of a good, and so forth; a political system voting for the next president. All of these systems have individual entities that are heterogeneous and acquire information according to a unique history about the world in which they live. That is not a world that Newton could deal with. There’s a very famous quote where he says something like, I have been able to understand the motion of the planets, but I will never understand the madness of men. What Newton was saying is, I don’t understand complexity.

 

http://nautil.us/issue/23/dominoes/ingenious-david-krakauer


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Thinking Ahead - Essays on Big Data, Digital Revolution, and Participatory Market Society

Thinking Ahead - Essays on Big Data, Digital Revolution, and Participatory Market Society | Edgar Analytics & Complex Systems | Scoop.it

The rapidly progressing digital revolution is now touching the foundations of the governance of societal structures. Humans are on the verge of evolving from consumers to prosumers, and old, entrenched theories – in particular sociological and economic ones – are falling prey to these rapid developments. The original assumptions on which they are based are being questioned. Each year we produce as much data as in the entire human history - can we possibly create a global crystal ball to predict our future and to optimally govern our world? Do we need wide-scale surveillance to understand and manage the increasingly complex systems we are constructing, or would bottom-up approaches such as self-regulating systems be a better solution to creating a more innovative, more successful, more resilient, and ultimately happier society? Working at the interface of complexity theory, quantitative sociology and Big Data-driven risk and knowledge management, the author advocates the establishment of new participatory systems in our digital society to enhance coordination, reduce conflict and, above all, reduce the “tragedies of the commons,” resulting from the methods now used in political, economic and management decision-making.

 

Thinking Ahead - Essays on Big Data, Digital Revolution, and Participatory Market Society
Authors: Dirk Helbing
ISBN: 978-3-319-15077-2 (Print) 978-3-319-15078-9 (Online)

http://www.pks.mpg.de/mpi-doc/sodyn/physicist-language/ ;


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Responding to complexity in socio-economic systems: How to build a smart and resilient society?

The world is changing at an ever-increasing pace. And it has changed in a much more fundamental way than one would think, primarily because it has become more connected and interdependent than in our entire history. Every new product, every new invention can be combined with those that existed before, thereby creating an explosion of complexity: structural complexity, dynamic complexity, functional complexity, and algorithmic complexity. How to respond to this challenge? And what are the costs?

 

Responding to complexity in socio-economic systems: How to build a smart and resilient society?
Dirk Helbing

http://arxiv.org/abs/1504.03750


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From seconds to months: multi-scale dynamics of mobile telephone calls

Big Data on electronic records of social interactions allow approaching human behaviour and sociality from a quantitative point of view with unforeseen statistical power. Mobile telephone Call Detail Records (CDRs), automatically collected by telecom operators for billing purposes, have proven especially fruitful for understanding one-to-one communication patterns as well as the dynamics of social networks that are reflected in such patterns. We present an overview of empirical results on the multi-scale dynamics of social dynamics and networks inferred from mobile telephone calls. We begin with the shortest timescales and fastest dynamics, such as burstiness of call sequences between individuals, and "zoom out" towards longer temporal and larger structural scales, from temporal motifs formed by correlated calls between multiple individuals to long-term dynamics of social groups. We conclude this overview with a future outlook.

 

From seconds to months: multi-scale dynamics of mobile telephone calls
Jari Saramaki, Esteban Moro

http://arxiv.org/abs/1504.01479


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Personalized routing for multitudes in smart cities

Human mobility in a city represents a fascinating complex system that combines social interactions, daily constraints and random explorations. New collections of data that capture human mobility not only help us to understand their underlying patterns but also to design intelligent systems. Bringing us the opportunity to reduce traffic and to develop other applications that make cities more adaptable to human needs. In this paper, we propose an adaptive routing strategy which accounts for individual constraints to recommend personalized routes and, at the same time, for constraints imposed by the collectivity as a whole. Using big data sets recently released during the Telecom Italia Big Data Challenge, we show that our algorithm allows us to reduce the overall traffic in a smart city thanks to synergetic effects, with the participation of individuals in the system, playing a crucial role.

 

Personalized routing for multitudes in smart cities
De Domenico M, Lima A, González MC, Arenas A
EPJ Data Science 2015, 4 :1

http://dx.doi.org/10.1140/epjds/s13688-015-0038-0 ;


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Must Read Report: The Internet’s Latest Disruption – Knowledge.

Must Read Report: The Internet’s Latest Disruption – Knowledge. | Edgar Analytics & Complex Systems | Scoop.it
Know or die: risk and opportunity of Knowledge 2.0
“And the web stormed the enterprise and disrupted roles, tasks and jobs: it cast speed, openness, flexibility and efficiency throughout, sparing no business processes: manufacturing, logistic, accounting, customer relation management, lead generation…”
The digital mutation is also profoundly disrupting how knowledge is acquired, organized and shared. Knowledge is an intangible, yet strategic asset of any enterprise. With businesses becoming more virtual and dematerialized, its value is patently and rapidly growing. Continue reading →
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Saving Human Lives: What Complexity Science and Information Systems can Contribute

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

 

Saving Human Lives: What Complexity Science and Information Systems can Contribute
Dirk Helbing, Dirk Brockmann, Thomas Chadefaux, Karsten Donnay, Ulf Blanke, Olivia Woolley-Meza, Mehdi Moussaid, Anders Johansson, Jens Krause, Sebastian Schutte, Matjaž Perc

Journal of Statistical Physics
June 2014,

http://link.springer.com/article/10.1007/s10955-014-1024-9


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A Multi-Level Geographical Study of Italian Political Elections from Twitter Data

A Multi-Level Geographical Study of Italian Political Elections from Twitter Data | Edgar Analytics & Complex Systems | Scoop.it

In this paper we present an analysis of the behavior of Italian Twitter users during national political elections. We monitor the volumes of the tweets related to the leaders of the various political parties and we compare them to the elections results. Furthermore, we study the topics that are associated with the co-occurrence of two politicians in the same tweet. We cannot conclude, from a simple statistical analysis of tweet volume and their time evolution, that it is possible to precisely predict the election outcome (or at least not in our case of study that was characterized by a “too-close-to-call” scenario). On the other hand, we found that the volume of tweets and their change in time provide a very good proxy of the final results. We present this analysis both at a national level and at smaller levels, ranging from the regions composing the country to macro-areas (North, Center, South).

 

http://dx.doi.org/10.1371/journal.pone.0095809

Multi-Level Geographical Study of Italian Political Elections from Twitter Data

Caldarelli G, Chessa A, Pammolli F, Pompa G, Puliga M, et al.

PLoS ONE 9(5): e95809 (2014)


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Frontiers in Robotics and AI

Frontiers in Robotics and AI | Edgar Analytics & Complex Systems | Scoop.it

Frontiers in Robotics and AI is the first open-access community journal covering the fields of robotics and artificial intelligence and joins the growing “Frontiers in” journal series. Frontiers in Robotics and AI will make use of the unique Frontiers open-science platform for open-access publishing and research networking, which provides an equal opportunity to seek, share and create knowledge.

 

Current specialty sections and associated journals open for submissions to Frontiers in Robotics and AI include:

·        Biomedical Robotics (Specialty Chief Editor: Darwin Gordon Caldwell)
·        Bionics and Biomimetics (Specialty Chief Editor: Danilo Emilio De Rossi)
·        Computational Intelligence (Specialty Chief Editor: Mikhail Prokopenko)
·        Evolutionary Robotics (Specialty Chief Editor: Gusz Eiben)
·        Humanoid Robotics (Specialty Chief Editor: Giorgio Metta)
·        Multi-Robot Systems (Specialty Chief Editor: Herbert Glenn Tanner)
·        Neurorobotics (Specialty Chief Editors: Alois C Knoll and Florian Röhrbein)
·        Neuroengineering (Specialty Chief Editor: Laura Ballerini)
·        Sensor Fusion and Machine Perception (Specialty Chief Editor: Shashi Phoha)
·        Virtual Environments (Specialty Chief Editor: Mel Slater)

 

http://www.frontiersin.org/news/Frontiers_launches_a_new_open-access_journal_Frontiers_in_Robotics_and_AI/812


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What ants teach us about the brain, cancer and the Internet

What ants teach us about the brain, cancer and the Internet | Edgar Analytics & Complex Systems | Scoop.it

Ecologist Deborah Gordon studies ants wherever she can find them -- in the desert, in the tropics, in her kitchen ... In this fascinating talk, she explains her obsession with insects most of us would happily swat away without a second thought. She argues that ant life provides a useful model for learning about many other topics, including disease, technology and the human brain.


http://on.ted.com/h0Emb ;


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Unconventional Computation & Natural Computation 2014

The International Conference on Unconventional Computation and Natural Computation has been a forum where scientists with different backgrounds, yet sharing a common interest in novel forms of computation, human-designed computation inspired by nature, and the computational aspects of processes taking place in nature, meet and present their latest results.

 

Unconventional Computation & Natural Computation 2014
University of Western Ontario, London, Ontario, Canada, July 14-18

http://conferences.csd.uwo.ca/ucnc2014/


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PhD Student at ETH Zurich

preferably with a background in computer science or physics for the ambitious ERC Advanced Investigator Grant "Momentum – Modeling the Emergence of Social Complexity and Order: How Individual and Societal Complexity Co-Evolve".

The Momentum project is about creating emergent social intelligence based on computational evolution and learning. It aims to model and simulate social interactions between sophisticated agents with cognitive capabilities and the resulting complex social dynamics on the macro-level, including phenomena such as self-organization, emergence of cooperation, social norms, and culture. The successful applicant will focus on the more technical, computation-related aspects, but will actively interact with the other team members and should also acquire a high-level understanding of the topic.

 

https://pub.refline.ch//845721/2943/++publications++/1/index.html


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