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With DeepMind, Google Prepares For A Future Where We See Ourselves In ... - TechCrunch

With DeepMind, Google Prepares For A Future Where We See Ourselves In ... - TechCrunch | Edgar Analytics & Complex Systems | Scoop.it
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With DeepMind, Google Prepares For A Future Where We See Ourselves In ...
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More intelligent computing means more insightful data gathering and analysis, of course.
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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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“Waiting for Carnot”: Information and complexity

The relationship between information and complexity is analyzed using a detailed literature analysis. Complexity is a multifaceted concept, with no single agreed definition. There are numerous approaches to defining and measuring complexity and organization, all involving the idea of information. Conceptions of complexity, order, organization, and “interesting order” are inextricably intertwined with those of information. Shannon's formalism captures information's unpredictable creative contributions to organized complexity; a full understanding of information's relation to structure and order is still lacking. Conceptual investigations of this topic should enrich the theoretical basis of the information science discipline, and create fruitful links with other disciplines that study the concepts of information and complexity.

 

“Waiting for Carnot”: Information and complexity
David Bawden and Lyn Robinson

Journal of the Association for Information Science and Technology
Early View

http://dx.doi.org/10.1002/asi.23535


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Jeff Hawkins on Firing Up the Silicon Brain | WIRED

Jeff Hawkins on Firing Up the Silicon Brain | WIRED | Edgar Analytics & Complex Systems | Scoop.it
#maketechhuman Jeff Hawkins recently re-read his 2004 book On Intelligence, where the founder of Palm computing – the company that gave us the first handheld computer and later, first-generation smartphones – explains how the human brain learns. An electrical engineer by training, Hawkins had taken a deep interest in how the brain works and founded…

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Understanding Brains: Details, Intuition, and Big Data

Understanding Brains: Details, Intuition, and Big Data | Edgar Analytics & Complex Systems | Scoop.it

Understanding how the brain works requires a delicate balance between the appreciation of the importance of a multitude of biological details and the ability to see beyond those details to general principles. As technological innovations vastly increase the amount of data we collect, the importance of intuition into how to analyze and treat these data may, paradoxically, become more important.

 

Marder E (2015) Understanding Brains: Details, Intuition, and Big Data. PLoS Biol 13(5): e1002147. http://dx.doi.org/10.1371/journal.pbio.1002147 


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On the Optimality and Predictability of Cultural Markets with Social Influence

Social influence is ubiquitous in cultural markets, from book recommendations in Amazon, to song popularities in iTunes and the ranking of newspaper articles in the online edition of the New York Times to mention only a few. Yet social influence is often presented in a bad light, often because it supposedly increases market unpredictability.
Here we study a model of trial-offer markets, in which participants try products and later decide whether to purchase. We consider a simple policy which ranks the products by quality when presenting them to market participants. We show that, in this setting, market efficiency always benefits from social influence. Moreover, we prove that the market converges almost surely to a monopoly for the product of highest quality, making the market both predictable and asymptotically optimal. Computational experiments confirm that the quality ranking policy identifies "blockbusters" in reasonable time, outperforms other policies, and is highly predictable. These results indicate that social influence does not necessarily increase market unpredicatibility. The outcome really depends on how social influence is used.

 

On the Optimality and Predictability of Cultural Markets with Social Influence
Pascal Van Hentenryck, Andres Abeliuk, Franco Berbeglia, Gerardo Berbeglia

http://arxiv.org/abs/1505.02469


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Hierarchical organisation of Britain through percolation theory

Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations, which are the outcome of geographical, political and historical constraints. Using percolation theory on the street intersections and on the road network of Britain, we obtain hierarchies at different scales that are independent of administrative arrangements. Natural boundaries, such as islands and National Parks, consistently emerge at the largest/regional scales. Cities are devised through recursive percolations on each of the emerging clusters, but the system does not undergo a phase transition at the distance threshold at which cities can be defined. This specific distance is obtained by computing the fractal dimension of the clusters extracted at each distance threshold. We observe that the fractal dimension presents a maximum over all the different distance thresholds. The clusters obtained at this maximum are in very good correspondence to the morphological definition of cities given by satellite images, and by other methods previously developed by the authors (Arcaute et al. 2015).

 

Hierarchical organisation of Britain through percolation theory
Elsa Arcaute, Carlos Molinero, Erez Hatna, Roberto Murcio, Camilo Vargas-Ruiz, Paolo Masucci, Jiaqiu Wang, Michael Batty

http://arxiv.org/abs/1504.08318


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The Intrafirm Complexity of Systemically Important Financial Institutions

In November, 2011, the Financial Stability Board, in collaboration with the International Monetary Fund, published a list of 29 "systemically important financial institutions" (SIFIs). This designation reflects a concern that the failure of any one of them could have dramatic negative consequences for the global economy and is based on "their size, complexity, and systemic interconnectedness". While the characteristics of "size" and "systemic interconnectedness" have been the subject of a good deal of quantitative analysis, less attention has been paid to measures of a firm's "complexity." In this paper we take on the challenges of measuring the complexity of a financial institution and to that end explore the use of the structure of an individual firm's control hierarchy as a proxy for institutional complexity. The control hierarchy is a network representation of the institution and its subsidiaries. We show that this mathematical representation (and various associated metrics) provides a consistent way to compare the complexity of firms with often very disparate business models and as such may provide the foundation for determining a SIFI designation. By quantifying the level of complexity of a firm, our approach also may prove useful should firms need to reduce their level of complexity either in response to business or regulatory needs. Using a data set containing the control hierarchies of many of the designated SIFIs, we find that in the past two years, these firms have decreased their level of complexity, perhaps in response to regulatory requirements.

 

The Intrafirm Complexity of Systemically Important Financial Institutions
Robin L. Lumsdaine, Daniel N. Rockmore, Nicholas Foti, Gregory Leibon, J. Doyne Farmer

http://arxiv.org/abs/1505.02305


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Logistic Growth and Ergodic Properties of Urban Forms

Urban morphology has presented significant intellectual challenges to mathematicians and physicists ever since the eighteenth century, when Euler first explored the famous Konigsberg bridges problem. Many important regularities and allometries have been observed in urban studies, including Zipf's law and Gibrat's law, rendering cities attractive systems for analysis within statistical physics. Nevertheless, a broad consensus on how cities and their boundaries are defined is still lacking. Applying percolation theory to the street intersection space, we show that growth curves for the maximum cluster size of the largest cities in the UK and in California collapse to a single curve, namely the logistic. Subsequently, by introducing the concept of the condensation threshold, we show that natural boundaries of cities can be well defined in a universal way. This allows us to study and discuss systematically some of the allometries that are present in cities, thus casting light on the concept of ergodicity as related to urban street networks.

 

Logistic Growth and Ergodic Properties of Urban Forms
A. Paolo Masucci, Elsa Arcaute, Jiaqiu Wang, Erez Hatna, Kiril Stanilov, Michael Batty

http://arxiv.org/abs/1504.07380


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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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Information-Theoretic Inference of Common Ancestors

A directed acyclic graph (DAG) partially represents the conditional independence structure among observations of a system if the local Markov condition holds, that is if every variable is independent of its non-descendants given its parents. In general, there is a whole class of DAGs that represents a given set of conditional independence relations. We are interested in properties of this class that can be derived from observations of a subsystem only. To this end, we prove an information-theoretic inequality that allows for the inference of common ancestors of observed parts in any DAG representing some unknown larger system. More explicitly, we show that a large amount of dependence in terms of mutual information among the observations implies the existence of a common ancestor that distributes this information. Within the causal interpretation of DAGs, our result can be seen as a quantitative extension of Reichenbach’s principle of common cause to more than two variables. Our conclusions are valid also for non-probabilistic observations, such as binary strings, since we state the proof for an axiomatized notion of “mutual information” that includes the stochastic as well as the algorithmic version.

 

Information-Theoretic Inference of Common Ancestors
Bastian Steudel and Nihat Ay

Entropy 2015, 17(4), 2304-2327; http://dx.doi.org/10.3390/e17042304 ;


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25 Years of Self-Organized Criticality: Concepts and Controversies

Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attacted much comment, ranging from the very positive to the polemical. The other papers in this special issue (Aschwanden et al, 2014; McAteer et al, 2014; Sharma et al, 2015) showcase the considerable body of observations in solar, magnetospheric and fusion plasma inspired by the SOC idea, and expose the fertile role the new paradigm has played in approaches to modeling and understanding multiscale plasma instabilities. This very broad impact, and the necessary process of adapting a scientific hypothesis to the conditions of a given physical system, has meant that SOC as studied in these fields has sometimes differed significantly from the definition originally given by its creators. In Bak's own field of theoretical physics there are significant observational and theoretical open questions, even 25 years on (Pruessner, 2012). One aim of the present review is to address the dichotomy between the great reception SOC has received in some areas, and its shortcomings, as they became manifest in the controversies it triggered. Our article tries to clear up what we think are misunderstandings of SOC in fields more remote from its origins in statistical mechanics, condensed matter and dynamical systems by revisiting Bak, Tang and Wiesenfeld's original papers.

 

25 Years of Self-Organized Criticality: Concepts and Controversies
Nicholas Watkins, Gunnar Pruessner, Sandra Chapman, Norma Bock Crosby, Henrik Jensen

http://arxiv.org/abs/1504.04991


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Why You Shouldn't Try to Be Everywhere in Social Media

Why You Shouldn't Try to Be Everywhere in Social Media | Edgar Analytics & Complex Systems | Scoop.it
Jason Keath, Founder & CEO of Social Fresh, drops by the Content Pros Podcast today to discuss content via conference presentations and the advantages of keeping things simple.

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donhornsby's curator insight, April 28, 7:35 AM

(From the article): Don’t try to put content out on all social channels; it won’t do you any good. (highlight to tweet) Look at your community—everyone you do business with in one way or another. Where are they? If they aren’t on a particular social network, don’t spend your time and energy there.

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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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Why Our Genome and Technology Are Both Riddled With “Crawling Horrors”

Why Our Genome and Technology Are Both Riddled With “Crawling Horrors” | Edgar Analytics & Complex Systems | Scoop.it

When we build complex technologies, despite our best efforts and our desire for clean logic, they often end up being far messier than we intend. They often end up kluges: inelegant solutions that work just well enough. And a reason they end up being messy—despite being designed and engineered—is because fundamentally the way they grow and evolve is often more similar to biological systems than we realize.

 

http://nautil.us/blog/why-our-genome-and-technology-are-both-riddled-with-crawling-horrors


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What Makes A Good Data Visualization? - Information Is Beautiful

What Makes A Good Data Visualization? - Information Is Beautiful | Edgar Analytics & Complex Systems | Scoop.it
What are the four elements necessary for a good data visualization? Information is Beautiful founder David McCandless shares his experience.

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Antonio Figueiredo's curator insight, May 19, 6:21 AM

This data visualization model stresses four elements that help scientists make their data more visual.

Rescooped by Nuno Edgar Fernandes from COMPUTATIONAL THINKING and CYBERLEARNING
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This Incredible 3D Printed Robotic Lamp Follows Objects As They Move

This Incredible 3D Printed Robotic Lamp Follows Objects As They Move | Edgar Analytics & Complex Systems | Scoop.it
The future of 3D printing will undoubtedly play a major role in the development of robotic devices. The custom aspects that the technology provides make it a pe

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Optimal Census by Quorum Sensing

Bacteria regulate gene expression in response to changes in cell density in a process called quorum sensing. To synchronize their gene-expression programs, these bacteria need to glean as much information as possible about their cell density. Our study is the first to physically model the flow of information in a quorum-sensing microbial community, wherein the internal regulator of the individuals response tracks the external cell density via an endogenously generated shared signal. Combining information theory and Lagrangian formalism, we find that quorum-sensing systems can improve their information capabilities by tuning circuit feedbacks. Our analysis suggests that achieving information benefit via feedback requires dedicated systems to control gene expression noise, such as sRNA-based regulation.

 

Optimal Census by Quorum Sensing
Thibaud Taillefumier, Ned S. Wingreen

PLoS Comput Biol 11(5): e1004238. http://dx.doi.org/10.1371/journal.pcbi.1004238 ;


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Pablo Vicente Munuera's curator insight, May 17, 4:15 AM

Quorum sensing is an interesting concept!

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The Fractured Nature of British Politics

The outcome of the British General Election to be held in just over one week's time is widely regarded as the most difficult in living memory to predict. Current polls suggest that the two main parties are neck and neck but that there will be a landslide to the Scottish Nationalist Party with that party taking most of the constituencies in Scotland. The Liberal Democrats are forecast to loose more than half their seats and the fringe parties of whom the UK Independence Party is the biggest are simply unknown quantities. Much of this volatility relates to long-standing and deeply rooted cultural and nationalist attitudes that relate to geographical fault lines that have been present for 500 years or more but occasionally reveal themselves, at times like this. In this paper our purpose is to raise the notion that these fault lines are critical to thinking about regionalism, nationalism and the hierarchy of cities in Great Britain (excluding Northern Ireland). We use a percolation method (Arcaute et al. 2015) to reveal them that treats Britain as a giant cluster of related places each defined from the intersections of the road network at a very fine spatial scale. We break this giant cluster into a detailed hierarchy of sub-clusters by successively reducing a distance threshold which first breaks off some of the Scottish Islands and then reveals the very distinct nations and regions that make up Britain, all the way down to the definition of the largest cities that appear when the threshold reaches 300m. We use these percolation clusters to apportion the 2010 voting pattern to a new hierarchy of constituencies based on these clusters, and this gives us a picture of how Britain might vote on purely geographical lines. We then examine this voting pattern which provides us with some sense of how important the new configuration of political parties might be to the election next week.

 

The Fractured Nature of British Politics
Carlos Molinero, Elsa Arcaute, Duncan Smith, Michael Batty

http://arxiv.org/abs/1505.00217


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Multifractal to monofractal evolution of the London's street network

We perform a multifractal analysis of the evolution of London's street network from 1786 to 2010. First, we show that a single fractal dimension, commonly associated with the morphological description of cities, does not su ce to capture the dynamics of the system. Instead, for a proper characterization of such a dynamics, the multifractal spectrum needs to be considered. Our analysis reveals that London evolves from an inhomogeneous fractal structure, that can be described in terms of a multifractal, to a homogeneous one, that converges to monofractality. We argue that London's multifractal to monofracal evolution might be a special outcome of the constraint imposed on its growth by a green belt. Through a series of simulations, we show that multifractal objects, constructed through di usion limited aggregation, evolve towards monofractality if their growth is constrained by a non-permeable boundary.

 

Multifractal to monofractal evolution of the London's street network
Roberto Murcio, A. Paolo Masucci, Elsa Arcaute, Michael Batty

http://arxiv.org/abs/1505.02760


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How a well-adapted immune system is organized

The adaptive immune system uses the experience of past infections to prepare its limited repertoire of specialized receptors to protect organisms from future threats. What is the best way of doing this? Building a theoretical framework from first principles, we predict the composition of receptor repertoires that are optimally adapted to minimize the cost of infections from a given pathogenic environment. A naive repertoire can reach these optima through a biologically plausible competitive mechanism. Our findings explain how limited populations of immune receptors can self-organize to provide effective immunity against highly diverse pathogens. Our results also inform the design and interpretation of experiments surveying immune repertoires.

 

How a well-adapted immune system is organized
Andreas Mayer, Vijay Balasubramanian, Thierry Mora, and Aleksandra M. Walczak

http://dx.doi.org/10.1073/pnas.1421827112 ;


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Neural Computations Mediating One-Shot Learning in the Human Brain

There are at least two distinct learning strategies for identifying the relationship between a cause and its consequence: (1) incremental learning, in which we gradually acquire knowledge through trial and error, and (2) one-shot learning, in which we rapidly learn from only a single pairing of a potential cause and a consequence. Little is known about how the brain switches between these two forms of learning. In this study, we provide evidence that the amount of uncertainty about the relationship between cause and consequence mediates the transition between incremental and one-shot learning. Specifically, the more uncertainty there is about the causal relationship, the higher the learning rate that is assigned to that stimulus. By imaging the brain while participants were performing the learning task, we also found that uncertainty about the causal association is encoded in the ventrolateral prefrontal cortex and that the degree of coupling between this region and the hippocampus increases during one-shot learning. We speculate that this prefrontal region may act as a “switch,” turning on and off one-shot learning as required.

 

Lee SW, O’Doherty JP, Shimojo S (2015) Neural Computations Mediating One-Shot Learning in the Human Brain. PLoS Biol 13(4): e1002137. http://dx.doi.org/10.1371/journal.pbio.1002137 ;


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When Money Learns to Fly: Towards Sensing as a Service Applications Using Bitcoin

Sensing-as-a-Service (S2aaS) is an emerging Internet of Things (IOT) business model pattern. To be technically feasible and to effectively allow for broad adoption, S2aaS implementations have to overcome manifold systemic hurdles, specifically regarding payment and sensor identification. In an effort to overcome these hurdles, we propose Bitcoin as protocol for S2aaS networks. To lay the groundwork and start the conversation about disruptive changes that Bitcoin technology could bring to S2aaS concepts and IOT in general, we identify and discuss the core characteristics that could drive those changes. We present a conceptual example and describe the basic process of exchanging data for cash using Bitcoin.

 

When Money Learns to Fly: Towards Sensing as a Service Applications Using Bitcoin
Kay Noyen, Dirk Volland, Dominic Wörner, Elgar Fleisch

http://arxiv.org/abs/1409.5841


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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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Thermodynamics of firms' growth

The distribution of firms' growth and firms' sizes is a topic under intense scrutiny. In this paper we show that a thermodynamic model based on the Maximum Entropy Principle, with dynamical prior information, can be constructed that adequately describes the dynamics and distribution of firms' growth. Our theoretical framework is tested against a comprehensive data-base of Spanish firms, which covers to a very large extent Spain's economic activity with a total of 1,155,142 firms evolving along a full decade. We show that the empirical exponent of Pareto's law, a rule often observed in the rank distribution of large-size firms, is explained by the capacity of the economic system for creating/destroying firms, and can be used to measure the health of a capitalist-based economy. Indeed, our model predicts that when the exponent is larger that 1, creation of firms is favored; when it is smaller that 1, destruction of firms is favored instead; and when it equals 1 (matching Zipf's law), the system is in a full macroeconomic equilibrium, entailing "free" creation and/or destruction of firms. For medium and smaller firm-sizes, the dynamical regime changes; the whole distribution can no longer be fitted to a single simple analytic form and numerical prediction is required. Our model constitutes the basis of a full predictive framework for the economic evolution of an ensemble of firms that can be potentially used to develop simulations and test hypothetical scenarios, as economic crisis or the response to specific policy measures.

 

Thermodynamics of firms' growth
Eduardo Zambrano, Alberto Hernando, Aurelio Fernandez-Bariviera, Ricardo Hernando, Angelo Plastino

http://arxiv.org/abs/1504.07666


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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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