Information, Comp...
Follow
4.0K views | +2 today
Information, Complexity, Computation
Your new post is loading...
Your new post is loading...
Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science
Scoop.it!

The Heart as a Complex Adaptive System

The Heart as a Complex Adaptive System | Information, Complexity, Computation | Scoop.it

There is mounting evidence that the heart is a system onto itself and that it is intimately intertwined with the nervous and endocrine system residing within its borders. The capacity of self-organized systems to adapt is embodied in the functional organization of the intrinsic control mechanisms. How these regulatory subsystems communicate and how uncoupling of the hierarchical organization results in loss of adaptive "fitness"remains a challenge in human biology. The principles by which "emergent properties" and functional order of a self-organizingsystem, such as the heart, achieve (homeo)dynamic stability provide a non-reductionist framework for understanding how biological system adapts to imposed internal and external stresses, e.g., ischemia, organ/tissue transplantation. In particular, the newly emergent dynamics of cardiac rhythm observed after the heart is transplanted may reflect a more stable,versatile and adaptive (as per "law of requisite variety") bipartite whole. The integrative action of the living organism can not be gotten from their concatenated fractions but is evolved "relationally", i.e., it emanates from emergent internal requirements of the constitutive parts.

J. Yasha Kresh, Igor Izrailtyan, Andrew S. Wechsler 
Depts. of Cardiothoracic Surgery and Medicine 
MCP-Hahnemann School of Medicine / Drexel University, Philadelphia, PA


Via Bernard Ryefield, NESS
more...
june holley's curator insight, January 7, 2014 8:09 AM

The heart can help us understand self-organization.

Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science
Scoop.it!

BBC Radio 4 - In Our Time, Complexity

BBC Radio 4 - In Our Time, Complexity | Information, Complexity, Computation | Scoop.it

Melvyn Bragg and his guests discuss complexity and how it can help us understand the world around us. When living beings come together and act in a group, they do so in complicated and unpredictable ways: societies often behave very differently from the individuals within them. Complexity was a phenomenon little understood a generation ago, but research into complex systems now has important applications in many different fields, from biology to political science. Today it is being used to explain how birds flock, to predict traffic flow in cities and to study the spread of diseases.


Via Bernard Ryefield, NESS
more...
ComplexInsight's curator insight, January 12, 2014 1:43 AM

You know a topic or meme has migrated into cultural hype-scape when Melvyn Bragg discusses it on Radio 4. However it's good to see complex adaptive systems research getting  considered coverage outside of the likes of Scientific American and New Scientist who have long promoted balanced views of the field.

Rescooped by Eugene Ch'ng from Papers
Scoop.it!

An exploration of social identity: The geography and politics of news-sharing communities in twitter

The importance of collective social action in current events is manifest in the Arab Spring and Occupy movements. Electronic social media have become a pervasive channel for social interactions, and a basis of collective social response to information. The study of social media can reveal how individual actions combine to become the collective dynamics of society. Characterizing the groups that form spontaneously may reveal both how individuals self-identify and how they will act together. Here we map the social, political, and geographical properties of news-sharing communities on Twitter, a popular microblogging platform. We track user-generated messages that contain links to New York Times online articles and we label users according to the topic of the links they share, their geographic location, and their self-descriptive keywords. When users are clustered based on who follows whom in Twitter, we find social groups separate by whether they are interested in local (NY), national (US) or global (cosmopolitan) issues. The national group subdivides into liberal, conservative and other, the latter being a diverse but mostly business oriented group with sports, arts, and other splinters. The national political groups are based across the US but are distinct from the national group that is broadly interested in a variety of topics. A person who is cosmopolitan associates with others who are cosmopolitan, and a US liberal/conservative associates with others who are US liberal/conservative, creating separated social groups with those identities. The existence of “citizens” of local, national, and cosmopolitan communities is a basis for dialog and action at each of these levels of societal organization.

 

An exploration of social identity: The geography and politics of news-sharing communities in twitter
AmaÇ HerdaĞdelen, Wenyun Zuo, Alexander Gard-Murray, Yaneer Bar-Yam

Complexity
Volume 19, Issue 2, pages 10–20, November/December 2013

http://dx.doi.org/10.1002/cplx.21457


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook

A crucial task in the analysis of on-line social-networking systems is to identify important people --- those linked by strong social ties --- within an individual's network neighborhood. Here we investigate this question for a particular category of strong ties, those involving spouses or romantic partners. We organize our analysis around a basic question: given all the connections among a person's friends, can you recognize his or her romantic partner from the network structure alone? Using data from a large sample of Facebook users, we find that this task can be accomplished with high accuracy, but doing so requires the development of a new measure of tie strength that we term `dispersion' --- the extent to which two people's mutual friends are not themselves well-connected. The results offer methods for identifying types of structurally significant people in on-line applications, and suggest a potential expansion of existing theories of tie strength.

 

Romantic Partnerships and the Dispersion of Social Ties: A Network Analysis of Relationship Status on Facebook
Lars Backstrom, Jon Kleinberg

http://arxiv.org/abs/1310.6753


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Geo-located Twitter as the proxy for global mobility patterns

In the advent of a pervasive presence of location sharing services researchers gained an unprecedented access to the direct records of human activity in space and time. This paper analyses geo-located Twitter messages in order to uncover global patterns of human mobility. Based on a dataset of almost a billion tweets recorded in 2012 we estimate volumes of international travelers in respect to their country of residence. We examine mobility profiles of different nations looking at the characteristics such as mobility rate, radius of gyration, diversity of destinations and a balance of the inflows and outflows. The temporal patterns disclose the universal seasons of increased international mobility and the peculiar national nature of overseen travels. Our analysis of the community structure of the Twitter mobility network, obtained with the iterative network partitioning, reveals spatially cohesive regions that follow the regional division of the world. Finally, we validate our result with the global tourism statistics and mobility models provided by other authors, and argue that Twitter is a viable source to understand and quantify global mobility patterns.

 

Geo-located Twitter as the proxy for global mobility patterns
Bartosz Hawelka, Izabela Sitko, Euro Beinat, Stanislav Sobolevsky, Pavlos Kazakopoulos, Carlo Ratti

http://arxiv.org/abs/1311.0680


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Designing complex dynamics in cellular automata with memory

Since their inception at Macy conferences in later 1940s, complex systems have remained the most controversial topic of interdisciplinary sciences. The term "complex system" is the most vague and liberally used scientific term. Using elementary cellular automata (ECA), and exploiting the CA classification, we demonstrate elusiveness of "complexity" by shifting space-time dynamics of the automata from simple to complex by enriching cells with memory. This way, we can transform any ECA class to another ECA class — without changing skeleton of cell-state transition function — and vice versa by just selecting a right kind of memory. A systematic analysis displays that memory helps "discover" hidden information and behavior on trivial — uniform, periodic, and nontrivial — chaotic, complex — dynamical systems.

 

Martinez, G. J., Adamatzky, A. and Alonso-Sanz, R. (2013) Designing complex dynamics in cellular automata with memory. International Journal of Bifurcation and Chaos, 23 (10). p. 1330035. ISSN 0218-1274

http://eprints.uwe.ac.uk/21980/


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Escaping the poverty trap: modeling the interplay between economic growth and the ecology of infectious disease

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, treatment capacity, etc.) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into ``poverty traps'' of poor health and poor economy. Here, using a simplified coupled disease-economic model with endogenous capital growth we demonstrate the formation of poverty traps, as well as ways to escape them. We suggest two possible mechanisms of escape both motivated by empirical data: one, through an influx of capital (development aid), and another through changing the percentage of GDP spent on healthcare. We find that a large influx of capital is successful in escaping the poverty trap, but increasing health spending alone is not. Our results demonstrate that escape from a poverty trap may be possible, and carry important policy implications in the world-wide distribution of aid and within-country healthcare spending.

 

Escaping the poverty trap: modeling the interplay between economic growth and the ecology of infectious disease
Georg M. Goerg, Oscar Patterson-Lomba, Laurent Hébert-Dufresne, Benjamin M. Althouse

http://arxiv.org/abs/1311.4079


Via Complexity Digest
more...
No comment yet.
Scooped by Eugene Ch'ng
Scoop.it!

5 keys to great nonverbal communication

5 keys to great nonverbal communication | Information, Complexity, Computation | Scoop.it
An experiment proves that a few differences in body language can make a huge difference in how well an audience takes in what a presenter says.
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Social Influence and the Collective Dynamics of Opinion Formation

Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

 

Social Influence and the Collective Dynamics of Opinion Formation
Mehdi Moussaid, Juliane E. Kaemmer, Pantelis P. Analytis, Hansjoerg Neth

http://arxiv.org/abs/1311.3475


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from CxBooks
Scoop.it!

Leaders Eat Last: Why Some Teams Pull Together and Others Don’t: Simon Sinek

Leaders Eat Last: Why Some Teams Pull Together and Others Don’t

~ Simon Sinek (author) More about this product
List Price: $27.95
Price: $16.41
You Save: $11.54 (41%)

Why do only a few people get to say “I love my job”? It seems unfair that finding fulfillment at work is like winning a lottery; that only a few lucky ones get to feel valued by their organizations, to feel like they belong.

Imagine a world where almost everyone wakes up inspired to go to work, feels trusted and valued during the day, then returns home feeling fulfilled.

This is not a crazy, idealized notion. Today, in many successful organizations, great leaders are creating environments in which people naturally work together to do remarkable things. 


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Experimental evidence for the influence of group size on cultural complexity

The remarkable ecological and demographic success of humanity is largely attributed to our capacity for cumulative culture1, 2, 3. The accumulation of beneficial cultural innovations across generations is puzzling because transmission events are generally imperfect, although there is large variance in fidelity. Events of perfect cultural transmission and innovations should be more frequent in a large population4. As a consequence, a large population size may be a prerequisite for the evolution of cultural complexity4, 5, although anthropological studies have produced mixed results6, 7, 8, 9 and empirical evidence is lacking10. Here we use a dual-task computer game to show that cultural evolution strongly depends on population size, as players in larger groups maintained higher cultural complexity. We found that when group size increases, cultural knowledge is less deteriorated, improvements to existing cultural traits are more frequent, and cultural trait diversity is maintained more often. Our results demonstrate how changes in group size can generate both adaptive cultural evolution and maladaptive losses of culturally acquired skills. As humans live in habitats for which they are ill-suited without specific cultural adaptations11, 12, it suggests that, in our evolutionary past, group-size reduction may have exposed human societies to significant risks, including societal collapse13.

 

Experimental evidence for the influence of group size on cultural complexity
• Maxime Derex, Marie-Pauline Beugin, Bernard Godelle & Michel Raymond

Nature 503, 389–391 (21 November 2013) http://dx.doi.org/10.1038/nature12774


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Early-warning signals of topological collapse in interbank networks

The financial crisis clearly illustrated the importance of characterizing the level of ‘systemic’ risk associated with an entire credit network, rather than with single institutions. However, the interplay between financial distress and topological changes is still poorly understood. Here we analyze the quarterly interbank exposures among Dutch banks over the period 1998–2008, ending with the crisis. After controlling for the link density, many topological properties display an abrupt change in 2008, providing a clear – but unpredictable – signature of the crisis. By contrast, if the heterogeneity of banks' connectivity is controlled for, the same properties show a gradual transition to the crisis, starting in 2005 and preceded by an even earlier period during which anomalous debt loops could have led to the underestimation of counter-party risk. These early-warning signals are undetectable if the network is reconstructed from partial bank-specific data, as routinely done. We discuss important implications for bank regulatory policies.


Via Claudia Mihai, Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Coexistence of critical regimes in interconnected networks

Networks in the real world do not exist as isolated entities, but they are often part of more complicated structures composed of many interconnected network layers. Recent studies have shown that such mutual dependence makes real networked systems exposed to potentially catastrophic failures, and thus there is a urgent necessity to better understand the mechanisms at the basis of this fragility. The theoretical approach to this problem is based on the study of the nature of the phase transitions associated to critical phenomena running on interconnected networks. In particular, it has been shown that many critical phenomena of continuous nature in isolated networks become instead discontinuous, and thus catastrophic, in multi-layer networks when the strength of the interconnections is sufficiently large. In this paper, we show that four main ingredients determine the critical features of a random interconnected network: the strength of the interconnections, the first two moments of the degree distribution of the entire network, and the correlation between intra- and inter-layer degrees. Different mixtures of these ingredients change the location of the critical points, and lead to the emergence a very rich scenario where phase transitions can be either discontinuous or continuous and different regimes can disappear or even coexist.

 

Coexistence of critical regimes in interconnected networks
Filippo Radicchi

http://arxiv.org/abs/1311.7031


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Non-Equilibrium Social Science
Scoop.it!

Philosophy of Complex Systems (Book in PDF)


Via António F Fonseca, NESS
more...
No comment yet.
Scooped by Eugene Ch'ng
Scoop.it!

Mozilla: Native code? No, it's JavaScript, only it's BLAZING FAST

Mozilla: Native code? No, it's JavaScript, only it's BLAZING FAST | Information, Complexity, Computation | Scoop.it
New tech promises browser apps at near native speed
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Connection, Connection, Connection…

There are approximately 86 billion neurons in the human brain. Over the past decades, we have made enormous progress in understanding their molecular, genetic, and structural makeup as well as their function. However, the real power of the central nervous system lies in the smooth coordination of large numbers of neurons. Neurons are thus organized on many different scales, from small microcircuits and assemblies all the way to regional brain networks. To interact effectively on all these levels, neurons, nuclei, cortical columns, and larger areas need to be connected. The study of neuronal connectivity has expanded rapidly in past years. Large research groups have recently joined forces and formed consortia to tackle the difficult problems of how to experimentally investigate connections in the brain and how to analyze and make sense of the enormous amount of data that arises in the process.
This year's neuroscience special issue is devoted to general and also several more specific aspects of research on connectivity in the brain. We invited researchers to review the most recent progress in their fields and to provide us with an outlook on what the future may hold in store.

 

Connection, Connection, Connection…
Peter Stern

Science 1 November 2013:
Vol. 342 no. 6158 p. 577
http://dx.doi.org/10.1126/science.342.6158.577


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Zipf's law unzipped

Introduction and background. The outcome of a random process is often well described by a bell-shaped curve, the normal distribution. Some hundred years ago, it was noticed that things like the richness among people, town sizes, surnames, and the frequency of words have different, broader distributions. The figure shows the probability of finding a word which occurs k times in a novel. If the words were distributed according to normal expectations, they would fall on the full curve in the figure. Many, more or less system-specific, proposals for the deviation from normal have been suggested under names such as 'rich gets richer', 'principle of least effort', 'preferential attachment' and 'independent proportional growth'. Here, it is argued that the phenomenon is connected to a more ubiquitous random group formation. A group is like a soccer team with positions to fill. You want the right player in the right position. Thus, unlike the normal distribution where you pick a player for the team, one now tries to pick a player for a position in the team.
Main results. Information theory is used to find the most likely distribution of group sizes given the number of objects, groups and the number of objects in the largest group. The result is the dashed curve in the figure. The same striking agreement is found for all data sets investigated.
Wider implications. This paper gives a new starting point for the understanding of Zipf-type phenomena.

 

Zipf's law unzipped

Seung Ki Baek et al 2011 New J. Phys. 13 043004 http://dx.doi.org/10.1088/1367-2630/13/4/043004


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

The Math of Segregation » American Scientist

The Math of Segregation » American Scientist | Information, Complexity, Computation | Scoop.it

In the 1960s Schelling devised a simple model in which a mixed group of people spontaneously segregates by race even though no one in the population desires that outcome. Initially, black and white families are randomly distributed. At each step in the modeling process the families examine their immediate neighborhood and either stay put or move elsewhere depending on whether the local racial composition suits their preferences. The procedure is repeated until everyone finds a satisfactory home (or until the simulator’s patience is exhausted).


Via Bernard Ryefield, Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

A Comparison of Tram Priority at Signalized Intersections

We study tram priority at signalized intersections using a stochastic cellular automaton model for multimodal traffic flow. We simulate realistic traffic signal systems, which include signal linking and adaptive cycle lengths and split plans, with different levels of tram priority. We find that tram priority can improve service performance in terms of both average travel time and travel time variability. We consider two main types of tram priority, which we refer to as full and partial priority. Full tram priority is able to guarantee service quality even when traffic is saturated, however, it results in significant costs to other road users. Partial tram priority significantly reduces tram delays while having limited impact on other traffic, and therefore achieves a better result in terms of the overall network performance. We also study variations in which the tram priority is only enforced when trams are running behind schedule, and we find that those variations retain almost all of the benefit for tram operations but with reduced negative impact on the network.

 

A Comparison of Tram Priority at Signalized Intersections
Lele Zhang, Timothy Garoni

http://arxiv.org/abs/1311.3590


Via Complexity Digest
more...
No comment yet.
Scooped by Eugene Ch'ng
Scoop.it!

The Power of Connection

The Power of Connection | Information, Complexity, Computation | Scoop.it
What will happen when there are more active mobile phones than people on the planet? What will that mean for the global economy?We’re about to find out.Next year is the year that active mobile and
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Graph measures and network robustness

Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to continue to perform well when it is subject to failures or attacks. In this paper we survey a large amount of robustness measures on simple, undirected and unweighted graphs, in order to offer a tool for network administrators to evaluate and improve the robustness of their network. The measures discussed in this paper are based on the concepts of connectivity (including reliability polynomials), distance, betweenness and clustering. Some other measures are notions from spectral graph theory, more precisely, they are functions of the Laplacian eigenvalues. In addition to surveying these graph measures, the paper also contains a discussion of their functionality as a measure for topological network robustness.

 

Graph measures and network robustness
W. Ellens, R.E. Kooij

http://arxiv.org/abs/1311.5064


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Escaping the poverty trap: modeling the interplay between economic growth and the ecology of infectious disease

The dynamics of economies and infectious disease are inexorably linked: economic well-being influences health (sanitation, nutrition, treatment capacity, etc.) and health influences economic well-being (labor productivity lost to sickness and disease). Often societies are locked into ``poverty traps'' of poor health and poor economy. Here, using a simplified coupled disease-economic model with endogenous capital growth we demonstrate the formation of poverty traps, as well as ways to escape them. We suggest two possible mechanisms of escape both motivated by empirical data: one, through an influx of capital (development aid), and another through changing the percentage of GDP spent on healthcare. We find that a large influx of capital is successful in escaping the poverty trap, but increasing health spending alone is not. Our results demonstrate that escape from a poverty trap may be possible, and carry important policy implications in the world-wide distribution of aid and within-country healthcare spending.

 

Escaping the poverty trap: modeling the interplay between economic growth and the ecology of infectious disease
Georg M. Goerg, Oscar Patterson-Lomba, Laurent Hébert-Dufresne, Benjamin M. Althouse

http://arxiv.org/abs/1311.4079


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Social Learning Strategies in Networked Groups

When making decisions, humans can observe many kinds of information about others' activities, but their effects on performance are not well understood. We investigated social learning strategies using a simple problem-solving task in which participants search a complex space, and each can view and imitate others' solutions. Results showed that participants combined multiple sources of information to guide learning, including payoffs of peers' solutions, popularity of solution elements among peers, similarity of peers' solutions to their own, and relative payoffs from individual exploration. Furthermore, performance was positively associated with imitation rates at both the individual and group levels. When peers' payoffs were hidden, popularity and similarity biases reversed, participants searched more broadly and randomly, and both quality and equity of exploration suffered. We conclude that when peers' solutions can be effectively compared, imitation does not simply permit scrounging, but it can also facilitate propagation of good solutions for further cumulative exploration.

 

Social Learning Strategies in Networked Groups

Thomas N. Wisdom, Xianfeng Song and Robert L. Goldstone

Cognitive Science
Volume 37, Issue 8, pages 1383–1425, November/December 2013

http://dx.doi.org/10.1111/cogs.12052


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Failure mechanisms of load sharing complex systems

We investigate the failure mechanisms of load sharing complex systems. The system is composed of multiple nodes or components whose failures are determined based on the interaction of their respective strengths and loads (or capacity and demand respectively) as well as the ability of a component to share its load with its neighbors when needed. We focus on two distinct mechanisms to model the interaction between components' strengths and loads. The failure mechanisms of these two models demonstrate temporal scaling phenomena, phase transitions and multiple distinct failure modes excited by extremal dynamics. For critical ranges of parameters the models demonstrate power law and exponential failure patterns. We identify the similarities and differences between the two mechanisms and the implications of our results to the failure mechanisms of complex systems in the real world.

 

Failure mechanisms of load sharing complex systems
Shahnewaz Siddique, Vitali Volovoi

http://arxiv.org/abs/1311.6700


Via Complexity Digest
more...
No comment yet.
Rescooped by Eugene Ch'ng from Papers
Scoop.it!

Complexity measurement of natural and artificial languages

We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization and complexity based on specific diversity and message length.

 

Complexity measurement of natural and artificial languages
Gerardo Febres, Klaus Jaffe, Carlos Gershenson

http://arxiv.org/abs/1311.5427


Via Complexity Digest
more...
No comment yet.