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Entropy and equilibrium state of free market models

Entropy and equilibrium state of free market models | Papers | Scoop.it

Many recent models of trade dynamics use the simple idea of wealth exchanges among economic agents in order to obtain a stable or equilibrium distribution of wealth among the agents. In particular, a plain analogy compares the wealth in a society with the energy in a physical system, and the trade between agents to the energy exchange between molecules during collisions. In physical systems, the energy exchange among molecules leads to a state of equipartition of the energy and to an equilibrium situation where the entropy is a maximum. On the other hand, in a large class of exchange models, the system converges to a very unequal condensed state, where one or a few agents concentrate all the wealth of the society while the wide majority of agents shares zero or almost zero fraction of the wealth. So, in those economic systems a minimum entropy state is attained. We propose here an analytical model where we investigate the effects of a particular class of economic exchanges that minimize the entropy. By solving the model we discuss the conditions that can drive the system to a state of minimum entropy, as well as the mechanisms to recover a kind of equipartition of wealth.

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Inside Money, Procyclical Leverage, and Banking Catastrophes

We explore a model of the interaction between banks and outside investors in which the ability of banks to issue inside money (short-term liabilities believed to be convertible into currency at par) can generate a collapse in asset prices and widespread bank insolvency. The banks and investors share a common belief about the future value of certain long-term assets, but they have different objective functions; changes to this common belief result in portfolio adjustments and trade. Positive belief shocks induce banks to buy risky assets from investors, and the banks finance those purchases by issuing new short-term liabilities. Negative belief shocks induce banks to sell assets in order to reduce their chance of insolvency to a tolerably low level, and they supply more assets at lower prices, which can result in multiple market-clearing prices. A sufficiently severe negative shock causes the set of equilibrium prices to contract (in a manner given by a cusp catastrophe), causing prices to plummet discontinuously and banks to become insolvent. Successive positive and negative shocks of equal magnitude do not cancel; rather, a banking catastrophe can occur even if beliefs simply return to their initial state. Capital requirements can prevent crises by curtailing the expansion of balance sheets when beliefs become more optimistic, but they can also force larger price declines. Emergency asset price supports can be understood as attempts by a central bank to coordinate expectations on an equilibrium with solvency.

 
Brummitt CD, Sethi R, Watts DJ (2014) Inside Money, Procyclical Leverage, and Banking Catastrophes. PLoS ONE 9(8): e104219. http://dx.doi.org/10.1371/journal.pone.0104219
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Systems Thinking and the Future of Cities

Systems Thinking and the Future of Cities | Papers | Scoop.it

The idea that nothing exists in isolation−but only as part of a system−has long been embedded in folklore, religious scriptures, and common sense. Yet, systems dynamics as a science has yet to transform the way we conduct the public business. This article first briefly explores the question of why advances in systems theory have failed to transform public policy. The second part describes the ways in which our understanding of systems is growing−not so much from theorizing, but from practical applications in agriculture, building design, and medical science. The third part focuses on whether and how that knowledge and systems science can be deployed to improve urban governance in the face of rapid climate destabilization so that sustainability becomes the norm, not the occasional success story.


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Erika Harrison's curator insight, August 15, 7:49 PM

In Brief

The idea that nothing exists in isolation−but only as part of a system−has long been embedded in folklore, religious scriptures, and common sense. Yet, systems dynamics as a science has yet to transform the way we conduct the public business. This article first briefly explores the question of why advances in systems theory have failed to transform public policy. The second part describes the ways in which our understanding of systems is growing−not so much from theorizing, but from practical applications in agriculture, building design, and medical science. The third part focuses on whether and how that knowledge and systems science can be deployed to improve urban governance in the face of rapid climate destabilization so that sustainability becomes the norm, not the occasional success story.


Key Concepts

Reducing wholes to parts lies at the core of the scientific worldview we inherited from Galileo, Bacon, Descartes, and their modern acolytes in the sciences of economics, efficiency, and management.The decades between 1950 and 1980 were the grand era for systems theory. However despite a great deal of talk about systems, we continue to administer, organize, analyze, manage, and govern complex ecological systems as if they were a collection of isolated parts and not an indissoluble union of energy, water, soils, land, forests, biota, and air.Much of what we have learned about managing real systems began in agriculture. One of the most important lessons being that land is an evolving organism of interrelated parts soils, hydrology, biota, wildlife, plants, animals, and people.The challenge is to transition organized urban complexity built on an industrial model and designed for automobiles, sprawl, and economic growth into coherent, civil, and durable places.A systems perspective to urban governance is a lens by which we might see more clearly through the fog of change, and potentially better manage the complex cause and effect relationships between social and ecological phenomena. The application of systems offers at least six possibilities to improve urban governance.

 

A system is an interconnected set of elements that is coherently organized in a way that achieves something . . . . [it] must consist of three kinds of things: elements, interconnections, and a function or purpose.
—Donella Meadows, Thinking in Systems1

 

A system [is] (a) a set of units or elements interconnected so that changes in some elements or their relations produce changes in other parts of the system, and (b) the entire system exhibits properties and behaviors that are different from those of the parts.
—Robert Jervis, Systems Effects 2

 

One of the most important ideas in modern science is the idea of a system; and it is almost impossible to define.
—Garrett Hardin, The Cybernetics of Competition3

Tobias Beckwith's curator insight, August 16, 1:45 PM

One of the things that gives real wizards their "powers," is the ability to see the world as systems within systems within systems... and then finding the leverage points, where a small action in one part of the system might cause a very large response elsewhere...

 

This post and article discuss that whole idea in a bit more depth. I found it to be a good read.

Gary Bamford's curator insight, August 20, 2:08 AM

Non-linear futures.

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Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies

Emergence is a common phenomenon, and it is also a general and important concept in complex dynamic systems like artificial societies. Usually, artificial societies are used for assisting in resolving several complex social issues (e.g., emergency management, intelligent transportation system) with the aid of computer science. The levels of an emergence may have an effect on decisions making, and the occurrence and degree of an emergence are generally perceived by human observers. However, due to the ambiguity and inaccuracy of human observers, to propose a quantitative method to measure emergences in artificial societies is a meaningful and challenging task. This article mainly concentrates upon three kinds of emergences in artificial societies, including emergence of attribution, emergence of behavior, and emergence of structure. Based on information entropy, three metrics have been proposed to measure emergences in a quantitative way. Meanwhile, the correctness of these metrics has been verified through three case studies (the spread of an infectious influenza, a dynamic microblog network, and a flock of birds) with several experimental simulations on the Netlogo platform. These experimental results confirm that these metrics increase with the rising degree of emergences. In addition, this article also has discussed the limitations and extended applications of these metrics.


Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies
Mingsheng Tang  and Xinjun Mao

Entropy 2014, 16, 4583-4602; http://dx.doi.org/10.3390/e16084583

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Programmable self-assembly in a thousand-robot swarm

Self-assembly enables nature to build complex forms, from multicellular organisms to complex animal structures such as flocks of birds, through the interaction of vast numbers of limited and unreliable individuals. Creating this ability in engineered systems poses challenges in the design of both algorithms and physical systems that can operate at such scales. We report a system that demonstrates programmable self-assembly of complex two-dimensional shapes with a thousand-robot swarm. This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large-scale decentralized systems. This work advances the aim of creating artificial swarms with the capabilities of natural ones.


Programmable self-assembly in a thousand-robot swarm
Michael Rubenstein, Alejandro Cornejo, Radhika Nagpal

Science 15 August 2014:
Vol. 345 no. 6198 pp. 795-799
http://dx.doi.org/10.1126/science.1254295

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Eli Levine's curator insight, August 16, 1:31 PM

Imagine what we can do as a society with this way of thinking and feeling in our governing bodies. This isn't social engineering, but the submission to discovered, natural law in the society, environment, economy, and universe as a whole.

 

It's all one thing. 

 

Enjoy. 

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Artificial Life and the Web: WebAL Comes of Age

A brief survey is presented of the first 18 years of web-based Artificial Life ("WebAL") research and applications, covering the period 1995-2013. The survey is followed by a short discussion of common methodologies employed and current technologies relevant to WebAL research. The paper concludes with a quick look at what the future may hold for work in this exciting area.


Artificial Life and the Web: WebAL Comes of Age
Tim Taylor

http://arxiv.org/abs/1407.5719

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Collective Learning and Optimal Consensus Decisions in Social Animal Groups

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.

 

Kao AB, Miller N, Torney C, Hartnett A, Couzin ID (2014) Collective Learning and Optimal Consensus Decisions in Social Animal Groups. PLoS Comput Biol 10(8): e1003762. http://dx.doi.org/10.1371/journal.pcbi.1003762


Via Ashish Umre
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A method for building self-folding machines

Origami can turn a sheet of paper into complex three-dimensional shapes, and similar folding techniques can produce structures and mechanisms. To demonstrate the application of these techniques to the fabrication of machines, we developed a crawling robot that folds itself. The robot starts as a flat sheet with embedded electronics, and transforms autonomously into a functional machine. To accomplish this, we developed shape-memory composites that fold themselves along embedded hinges. We used these composites to recreate fundamental folded patterns, derived from computational origami, that can be extrapolated to a wide range of geometries and mechanisms. This origami-inspired robot can fold itself in 4 minutes and walk away without human intervention, demonstrating the potential both for complex self-folding machines and autonomous, self-controlled assembly.


A method for building self-folding machines
S. Felton, M. Tolley, E. Demaine, D. Rus, R. Wood

Science 8 August 2014:
Vol. 345 no. 6197 pp. 644-646
http://dx.doi.org/10.1126/science.1252610

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Cloudy With a Chance of War

Cloudy With a Chance of War | Papers | Scoop.it

He then sorted his “deadly quarrels” the way geologists classify earthquakes, ranking each “quarrel” according to the base-10 logarithm of the number of deaths it produced. The base-10 logarithm of a number describes how many times 10 must be multiplied to produce that number. A riot that leaves 100 dead in this system has a magnitude of 2 (the base—10—must be multiplied by itself to yield 100). And a conflict that kills 10 million people has a magnitude of 7 (multiplying seven tens will yield 10 million). Defining “deadly quarrels” on a logarithmic scale also served Richardson’s project to get people thinking about violence without illusion. Like the Richter scale for earthquakes, his logarithmic graphs let the reader see all quarrels, from murders to global war, as a single phenomenon on a single scale.


http://nautil.us/issue/15/turbulence/cloudy-with-a-chance-of-war

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The impact of network structure on innovation efficiency: An agent-based study in the context of innovation networks

This article investigates the impact of network structure on innovation efficiency by establishing a simulation model of innovation process in the context of innovation networks. The results indicate that short path lengths between vertices are conductive to high efficiency of explorative innovations, dense clusters are conductive to high efficiency of exploitative innovations, and high small-worldness is conductive to high efficiency of the hybrid of these two innovations. Moreover, we discussed the reason of the results and give some suggestions to innovators and innovation policy makers.


The impact of network structure on innovation efficiency: An agent-based study in the context of innovation networks
Lei Hua and Wenping Wang

Complexity

http://dx.doi.org/10.1002/cplx.21583

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Science vs Conspiracy: collective narratives in the age of (mis)information

The large availability of user provided contents on online social media facilitates people aggregation around common interests, worldviews and narratives. However, in spite of the enthusiastic rhetoric about the so called {\em wisdom of crowds}, unsubstantiated rumors -- as alternative explanation to main stream versions of complex phenomena -- find on the Web a natural medium for their dissemination. In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives -- i.e. main stream scientific and alternative news -- are consumed on Facebook. Through a thorough quantitative analysis, we show that distinct communities with similar information consumption patterns emerge around distinctive narratives. Moreover, consumers of alternative news (mainly conspiracy theories) result to be more focused on their contents, while scientific news consumers are more prone to comment on alternative news. We conclude our analysis testing the response of this social system to 4709 troll information -- i.e. parodistic imitation of alternative and conspiracy theories. We find that, despite the false and satirical vein of news, usual consumers of conspiracy news are the most prone to interact with them.


Science vs Conspiracy: collective narratives in the age of (mis)information
Alessandro Bessi, Mauro Coletto, George Alexandru Davidescu, Antonio Scala, Guido Caldarelli, Walter Quattrociocchi

http://arxiv-web3.library.cornell.edu/abs/1408.1667

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Charting culture

This animation distils hundreds of years of culture into just five minutes. A team of historians and scientists wanted to map cultural mobility, so they tracked the births and deaths of notable individuals like David, King of Israel, and Leonardo da Vinci, from 600 BC to the present day. Using them as a proxy for skills and ideas, their map reveals intellectual hotspots and tracks how empires rise and crumble

.


The information comes from Freebase, a Google-owned database of well-known people and places, and other catalogues of notable individuals. The visualization was created by Maximilian Schich (University of Texas at Dallas) and Mauro Martino (IBM).




https://www.youtube.com/watch?v=4gIhRkCcD4U&index=1&list=PL7yuGPz_odjMW3YfSRkFRjoDdGsTrZDyD 

Read Nature's news story: http://www.nature.com/news/1.15650

See Also: http://sco.lt/8by75F 


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Quantifying the semantics of search behavior before stock market moves

Internet search data may offer new possibilities to improve forecasts of collective behavior, if we can identify which parts of these gigantic search datasets are relevant. We introduce an automated method that uses data from Google and Wikipedia to identify relevant topics in search data before large events. Using stock market moves as a case study, our method successfully identifies historical links between searches related to business and politics and subsequent stock market moves. We find that the predictive value of these search terms has recently diminished, potentially reflecting increasing incorporation of Internet data into automated trading strategies. We suggest that extensions of these analyses could help draw links between search data and a range of other collective actions.

 

Quantifying the semantics of search behavior before stock market moves

C. Curmea, T. Preis, H.E. Stanley, and H.S. Moat
http://dx.doi.org/10.1073/pnas.1324054111

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How bird flocks are like liquid helium

How bird flocks are like liquid helium | Papers | Scoop.it

Mathematical model shows how hundreds of starlings coordinate their movements in flight.

A flock of starlings flies as one, a spectacular display in which each bird flits about as if in a well-choreographed dance. Everyone seems to know exactly when and where to turn. Now, for the first time, researchers have measured how that knowledge moves through the flock—a behavior that mirrors certain quantum phenomena of liquid helium.


Via Claudia Mihai
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Origin of symbol-using systems: speech, but not sign, without the semantic urge

Natural language—spoken and signed—is a multichannel phenomenon, involving facial and body expression, and voice and visual intonation that is often used in the service of a social urge to communicate meaning. Given that iconicity seems easier and less abstract than making arbitrary connections between sound and meaning, iconicity and gesture have often been invoked in the origin of language alongside the urge to convey meaning. To get a fresh perspective, we critically distinguish the origin of a system capable of evolution from the subsequent evolution that system becomes capable of. Human language arose on a substrate of a system already capable of Darwinian evolution; the genetically supported uniquely human ability to learn a language reflects a key contact point between Darwinian evolution and language. Though implemented in brains generated by DNA symbols coding for protein meaning, the second higher-level symbol-using system of language now operates in a world mostly decoupled from Darwinian evolutionary constraints. Examination of Darwinian evolution of vocal learning in other animals suggests that the initial fixation of a key prerequisite to language into the human genome may actually have required initially side-stepping not only iconicity, but the urge to mean itself. If sign languages came later, they would not have faced this constraint.


Origin of symbol-using systems: speech, but not sign, without the semantic urge
Martin I. Sereno

http://dx.doi.org/10.1098/rstb.2013.0303
Phil. Trans. R. Soc. B 19 September 2014 vol. 369 no. 1651 20130303

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Local rewiring rules for evolving complex networks

The effects of link rewiring are considered for the class of directed networks where each node has the same fixed out-degree. We model a network generated by three mechanisms that are present in various networked systems; growth, global rewiring and local rewiring. During a rewiring phase a node is randomly selected, one of its out-going edges is detached from its destination then re-attached to the network in one of two possible ways; either globally to a randomly selected node, or locally to a descendant of a descendant of the originally selected node. Although the probability of attachment to a node increases with its connectivity, the probability of detachment also increases, the result is an exponential degree distribution with a small number of outlying nodes that have extremely large degree. We explain these outliers by identifying the circumstances for which a set of nodes can grow to very high degree.

 

"Local rewiring rules for evolving complex networks"
Ewan R. Colman, Geoff J. Rodgers, arXiv:1408.3570, 2014
http://arxiv.org/abs/1408.3570

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JIDT: An information-theoretic toolkit for studying the dynamics of complex systems

Complex systems are increasingly being viewed as distributed information processing systems, particularly in the domains of computational neuroscience, bioinformatics and Artificial Life. This trend has resulted in a strong uptake in the use of (Shannon) information-theoretic measures to analyse the dynamics of complex systems in these fields. We introduce the Java Information Dynamics Toolkit (JIDT): a Google code project which provides a standalone, (GNU GPL v3 licensed) open-source code implementation for empirical estimation of information-theoretic measures from time-series data. While the toolkit provides classic information-theoretic measures (e.g. entropy, mutual information, conditional mutual information), it ultimately focusses on implementing higher-level measures for information dynamics. That is, JIDT focusses on quantifying information storage, transfer and modification, and the dynamics of these operations in space and time. For this purpose, it includes implementations of the transfer entropy and active information storage, their multivariate extensions and local or pointwise variants. JIDT provides implementations for both discrete and continuous-valued data for each measure, including various types of estimator for continuous data (e.g. Gaussian, box-kernel and Kraskov-Stoegbauer-Grassberger) which can be swapped at run-time due to Java's object-oriented polymorphism. Furthermore, while written in Java, the toolkit can be used directly in MATLAB, GNU Octave and Python. We present the principles behind the code design, and provide several examples to guide users

 

"JIDT: An information-theoretic toolkit for studying the dynamics of complex systems"
Joseph T. Lizier, arXiv:1408.3270, 2014
http://arxiv.org/abs/1408.3270

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Eli Levine's curator insight, August 19, 11:11 AM

This could be useful.

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The dynamics of correlated novelties

The dynamics of correlated novelties | Papers | Scoop.it

Novelties are a familiar part of daily life. They are also fundamental to the evolution of biological systems, human society, and technology. By opening new possibilities, one novelty can pave the way for others in a process that Kauffman has called “expanding the adjacent possible”. The dynamics of correlated novelties, however, have yet to be quantified empirically or modeled mathematically. Here we propose a simple mathematical model that mimics the process of exploring a physical, biological, or conceptual space that enlarges whenever a novelty occurs. The model, a generalization of Polya's urn, predicts statistical laws for the rate at which novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's law), as well as signatures of the process by which one novelty sets the stage for another. We test these predictions on four data sets of human activity: the edit events of Wikipedia pages, the emergence of tags in annotation systems, the sequence of words in texts, and listening to new songs in online music catalogues. By quantifying the dynamics of correlated novelties, our results provide a starting point for a deeper understanding of the adjacent possible and its role in biological, cultural, and technological evolution.

 

The dynamics of correlated novelties

F. Tria, V. Loreto, V. D. P. Servedio, & S. H. Strogatz

Scientific Reports 4, Article number: 5890

http://dx.doi.org/10.1038/srep05890

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Robustness and Evolvability of the Human Signaling Network

Biological systems are known to be robust and evolvable to internal mutations and external environmental changes. What causes these apparently contradictory properties? This study shows that the human signaling network can be decomposed into two structurally distinct subgroups of links that provide both evolvability to environmental changes and robustness against internal mutations. The decomposition of the human signaling network reveals an evolutionary design principle of the network, and also facilitates the identification of potential drug targets.


Kim J, Vandamme D, Kim J-R, Munoz AG, Kolch W, et al. (2014) Robustness and Evolvability of the Human Signaling Network. PLoS Comput Biol 10(7): e1003763. http://dx.doi.org/10.1371/journal.pcbi.1003763

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Limits on fundamental limits to computation

An indispensable part of our personal and working lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the past fifty years. Such Moore scaling now requires ever-increasing efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and increase our understanding of integrated-circuit scaling, here I review fundamental limits to computation in the areas of manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, I recapitulate how some limits were circumvented, and compare loose and tight limits. Engineering difficulties encountered by emerging technologies may indicate yet unknown limits.


Limits on fundamental limits to computation
Igor L. Markov
Nature 512, 147–154 (14 August 2014) http://dx.doi.org/10.1038/nature13570

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ComplexInsight's curator insight, August 15, 2:31 AM

Discussion of limits is key to creating new ideas - Igor Markov's paper is worth reading for exploring lmitations and engineering implications and to trigger off new discussions and ideas. Worth reading.

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Self-organization in complex systems as decision making

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems

 

Self-organization in complex systems as decision making
V.I. Yukalov, D. Sornette
arXiv:1408.1529, 2014
http://arxiv.org/abs/1408.1529

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Eli Levine's curator insight, August 16, 1:28 PM

Basically, the process of decision-making is apart of the system as a whole and not an externality. Where is the clear distinction between a user and the computer program that they choose to run? Can't it all be viewed as one thing? 

 

Amazing implications for governing and government relative to society. 

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Online collaboration: Scientists and the social network

Giant academic social networks have taken off to a degree that no one expected even a few years ago. A Nature survey explores why.
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Crowdsourcing Dialect Characterization through Twitter

We perform a large-scale analysis of language diatopic variation using geotagged microblogging datasets. By collecting all Twitter messages written in Spanish over more than two years, we build a corpus from which a carefully selected list of concepts allows us to characterize Spanish varieties on a global scale. A cluster analysis proves the existence of well defined macroregions sharing common lexical properties. Remarkably enough, we find that Spanish language is split into two superdialects, namely, an urban speech used across major American and Spanish citites and a diverse form that encompasses rural areas and small towns. The latter can be further clustered into smaller varieties with a stronger regional character.


Crowdsourcing Dialect Characterization through Twitter
Bruno Gonçalves, David Sánchez

10.1073/pnas.1407486111

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Competitive Dynamics on Complex Networks

Competitive Dynamics on Complex Networks | Papers | Scoop.it

We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.

 

Competitive Dynamics on Complex Networks

Jiuhua Zhao, Qipeng Liu, & Xiaofan Wang
Scientific Reports 4, Article number: 5858
http://dx.doi.org/10.1038/srep05858

 

 

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AleksBlumentals's curator insight, August 14, 2:39 AM

How do you discover Caseworthiness? 

 


Tom Cockburn's curator insight, August 14, 10:41 AM

Could be useful

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The human dynamic clamp as a paradigm for social interaction

The human dynamic clamp (HDC) is proposed as a general paradigm for studies of elementary forms of social behavior in complex biological systems. HDC enables parametric control of real-time bidirectional interaction between humans and empirically grounded theoretical models of coordination dynamics. It thus provides necessary experimental access for laboratory investigations, while preserving the reciprocity and open boundary conditions inherent in daily life social interactions. As proof of concept, different implementations are illustrated, ranging from coordination of rhythmic and discrete movements to adaptive and directed behaviors. The HDC may be a powerful tool for blending theory and experiment at different levels of description, from neuronal populations to cognition and social behavior.


The human dynamic clamp as a paradigm for social interaction
Guillaume Dumas, Gonzalo C. de Guzman, Emmanuelle Tognoli, and J. A. Scott Kelso

http://dx.doi.org/10.1073/pnas.1407486111

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Complexity and the Emergence of Physical Properties

Using the effective complexity measure, proposed by M. Gell-Mann and S. Lloyd, we give a quantitative definition of an emergent property. We use several previous results and properties of this particular information measure closely related to the random features of the entity and its regularities.


Complexity and the Emergence of Physical Properties
Miguel Angel Fuentes

Entropy 2014, 16(8), 4489-4496; http://dx.doi.org/10.3390/e16084489

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Costas Bouyioukos's curator insight, August 18, 12:56 PM

Interesting for those who look for emergent properties in biological systems!