Information, Complexity, Computation
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Information, Complexity, Computation
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Darwin’s extra sense: How mathematics is revolutionizing biology | Santa Fe Institute

Darwin’s extra sense: How mathematics is revolutionizing biology | Santa Fe Institute | Information, Complexity, Computation | Scoop.it
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Model resolution in complex systems simulation: Agent preferences, behavior, dynamics and n-tiered networks

Eugene Ch'ng's insight:

Agent-based modeling is a process of representing and simulating the intentions, behaviors and actions of complex systems with the goal of understanding specific phenomena related to the communications within complex systems that produce emergent behavior and self-organization, or for predicting spatial or behavioral patterns of individuals or groups of interacting entities. Agent-based modeling, also termed multi-agent systems, or in ecological simulation, individual-based models, spans simple to highly complex systems; their interactions can be difficult to implement and optimize programmatically, particularly when there could be hundreds of thousands of agents within a community that have multiple levels of communication. The resolution and the scale of simulation is an especially important component that could determine the accuracy of the models. This article focuses on the model resolution of complex systems, facilitated by an object-oriented communications framework, a foundation for the simulation of the fine resolution of the dynamics, behavior, preferences, interaction and n-tiered trophic networks, including the simulated environments they inhabit. It dissects individual agents with a view to modeling and simulating fine behaviors amongst a population of agent types in n-tiered networks, scalable to hundreds of thousands of species using mathematically defined behavior, efficient algorithms and adaptive data structures as support for the simulations.

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A mathematical model of the London riots and their policing

In August 2011, several areas of London experienced episodes of large-scale disorder, comprising looting, rioting and violence. Much subsequent discourse has questioned the adequacy of the police response, in terms of the resources available and strategies used. In this article, we present a mathematical model of the spatial development of the disorder, which can be used to examine the effect of varying policing arrangements. The model is capable of simulating the general emergent patterns of the events and focusses on three fundamental aspects: the apparently-contagious nature of participation; the distances travelled to riot locations; and the deterrent effect of policing. We demonstrate that the spatial configuration of London places some areas at naturally higher risk than others, highlighting the importance of spatial considerations when planning for such events. We also investigate the consequences of varying police numbers and reaction time, which has the potential to guide policy in this area.

 

A mathematical model of the London riots and their policing

Toby P. Davies, Hannah M. Fry, Alan G. Wilson & Steven R. Bishop

Scientific Reports 3, Article number: 1303 http://dx.doi.org/10.1038/srep01303


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Agent-based Modeling of Policies to Improve Urban Food Access for Low-income Populations

Despite advances in medical technology and public health practices over the past few decades, there has been a steady increase in the prevalence of chronic diseases like type 2 diabetes among low-income urban residents in the US. For this population, maintaining a diet consisting of nutritious foods is complicated by a number of physical and social barriers. In cities, a coalescence of social, spatial, and economic factors influence the availability of healthy food in any given place. The urban food environment contextualizes the structural and individual-level norms that drive daily decision-making about what to eat. Understanding and acting on the processes that reduce these residents' access to healthy foods will make for a healthier urban landscape. A new paper by M.J. Widener, S.S. Metcalf, and Y. Bar-Yam advances the discussion of food deserts by using an agent-based model to simulate the impact of various policy interventions on low-income households’ consumption of fresh fruits and vegetables.

 

M.J. Widener, S.S. Metcalf, and Y. Bar-Yam, Agent-based Modeling of Policies to Improve Urban Food Access for Low-income Populations. Applied Geography. 40 pp. 1-10. 2013.

http://www.necsi.edu/research/social/urbanfood/policies/


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Lauren Shigemasa's curator insight, January 23, 2014 1:31 AM

to be used as an example! This graph shows the Number of households in Buffalo, NY with fresh fruits and vegetables in stock given different mobile market distribution plans. the variation in numbers is astounding.

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New research to uncover nuances of networks | Santa Fe Institute

New research to uncover nuances of networks | Santa Fe Institute | Information, Complexity, Computation | Scoop.it
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Third European Ph.D. School on Mathematical Modeling of Complex Systems, 18-29 July 2013 | Third European Ph.D. School on Mathematical Modeling of Complex Systems, 18-29 July 2013

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The Potential of Connectivity in the 21st Century | Experts' Corner | Big Think

The Potential of Connectivity in the 21st Century | Experts' Corner | Big Think | Information, Complexity, Computation | Scoop.it
It’s strange to think how young the Internet is, considering its enormity and complexity, and yet how powerful it has become as a means to connect people from around the world and influence our everyday lives and society as a whole.

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Harold Thwaites's curator insight, February 13, 2013 2:39 AM

Some excellent insight here. Check out her documentary.

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Accelerating Discovery: Distilling Natural Laws from Experimental Data, from Physics to Biology

Collective Dynamics of Complex Systems Research Group Seminar Series
(Co-hosted by the Evolutionary Studies program and the Department of Electrical and Computer Engineering)
February 11, 2013
Hod Lipson (Mechanical and Aerospace Engineering, Cornell University)
"Accelerating Discovery: Distilling Natural Laws from Experimental Data, from Physics to Biology"

http://vimeo.com/59458466


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"A Hitchiker’s Guide to Complexity" by Dr Rachel Armstrong

“This talk offers a multi-disciplinary view of complexity from the perspective of an informed amateur – an ideas hitchhiker – curating concepts relevant to its philosophical, technological and cultural importance. These ideas are co-ordinates for a hitchhiker’s map that provokes discussion about the theory, method and application of complex systems in addressing cultural agendas and how they may work as a counter point to prevalent practices. Of particular interest is how complexity may offer alternative technological systems to machines, which shape our Modern era. Although complexity is still an emerging practice and not a ‘cure-all’ to the significant challenges that we face this century, it may offer a point of reflection on the processes that underpin human development – to identify opportunities where the interests of humanity and the environment may be one and the same – say for example, by considering the Earth to be a giant ‘natural’ supercomputer.”

 

On Wednesday 30th January, Dr Rachel Armstrong from the the University of Greenwich gave the CS4 talk “A Hitchiker’s Guide to Complexity”


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Move-by-Move Dynamics of the Advantage in Chess Matches Reveals Population-Level Learning of the Game

Move-by-Move Dynamics of the Advantage in Chess Matches Reveals Population-Level Learning of the Game | Information, Complexity, Computation | Scoop.it

The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player’s advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is 0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player’s advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments.


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How women organize social networks different from men

How women organize social networks different from men | Information, Complexity, Computation | Scoop.it

Superpositions of social networks, such as communication, friendship, or trade networks, are called multiplex networks, forming the structural backbone of human societies. Novel datasets now allow quantification and exploration of multiplex networks. Here we study gender-specific differences of a multiplex network from a complete behavioral dataset of an online-game society of about 300,000 players. On the individual level females perform better economically and are less risk-taking than males. Males reciprocate friendship requests from females faster than vice versa and hesitate to reciprocate hostile actions of females. On the network level females have more communication partners, who are less connected than partners of males. We find a strong homophily effect for females and higher clustering coefficients of females in trade and attack networks. Cooperative links between males are under-represented, reflecting competition for resources among males. These results confirm quantitatively that females and males manage their social networks in substantially different ways.


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The Power of Networks

The Power of Networks | Information, Complexity, Computation | Scoop.it
The World Economic Forum (WEF) is a Geneva-based non-profit organization best known for its Annual Meeting in Davos, Switzerland, the Annual Meeting of New Champions in China (Summer Davos) and the Summit on the Global Agenda in Dubai.
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Both information and social cohesion determine collective decisions in animal groups

During consensus decision making, individuals in groups balance personal information (based on their own past experiences) with social information (based on the behavior of other individuals), allowing the group to reach a single collective choice. Previous studies of consensus decision making processes have focused on the informational aspects of behavioral choice, assuming that individuals make choices based solely on their likelihood of being beneficial (e.g., rewarded). However, decisions by both humans and nonhuman animals systematically violate such expectations. Furthermore, the typical experimental paradigm of assessing binary decisions, those between two mutually exclusive options, confounds two aspects common to most group decisions: minimizing uncertainty (through the use of personal and social information) and maintaining group cohesion (for example, to reduce predation risk). Here we experimentally disassociate cohesion-based decisions from information-based decisions using a three-choice paradigm and demonstrate that both factors are crucial to understanding the collective decision making of schooling fish. 

 

Both information and social cohesion determine collective decisions in animal groups
Noam Miller, Simon Garnier, Andrew T. Hartnett, and Iain D. Couzin

http://dx.doi.org/10.1073/pnas.1217513110
PNAS February 25, 2013 201217513


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Miguel Nicolelis Says the Brain Is Not Computable, Bashes Kurzweil’s Singularity | MIT Technology Review

Miguel Nicolelis Says the Brain Is Not Computable, Bashes Kurzweil’s Singularity | MIT Technology Review | Information, Complexity, Computation | Scoop.it
A leading neuroscientist says Kurzweil’s Singularity isn’t going to happen. Instead, humans will assimilate machines.
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The Geography of Happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place

We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated over the course of several recent years on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-level measures such as obesity rates.

 

The Geography of Happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place

Lewis Mitchell, Kameron Decker Harris, Morgan R. Frank, Peter Sheridan Dodds, Christopher M. Danforth

http://arxiv.org/abs/1302.3299v2


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How Cells Know Where They Are

Development, regeneration, and even day-to-day physiology require plant and animal cells to make decisions based on their locations. The principles by which cells may do this are deceptively straightforward. But when reliability needs to be high—as often occurs during development—successful strategies tend to be anything but simple. Increasingly, the challenge facing biologists is to relate the diverse diffusible molecules, control circuits, and gene regulatory networks that help cells know where they are to the varied, sometimes stringent, constraints imposed by the need for real-world precision and accuracy.

 

How Cells Know Where They Are
Arthur D. Lander

Science 22 February 2013:
Vol. 339 no. 6122 pp. 923-927
http://dx.doi.org/10.1126/science.1224186


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7th Annual French Complex Systems Summer School

7th Annual French Complex Systems Summer School | Information, Complexity, Computation | Scoop.it

7th Annual French Complex Systems Summer School

"Collective Behaviour and Mobility in Complex Systems"
Le Havre, July 9th to 18th, 2013

http://www.iscpif.fr/CSSS2013


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Identifying trends in word frequency dynamics

The word-stock of a language is a complex dynamical system in which words can be created, evolve, and become extinct. Even more dynamic are the short-term fluctuations in word usage by individuals in a population. Building on the recent demonstration that word niche is a strong determinant of future rise or fall in word frequency, here we introduce a model that allows us to distinguish persistent from temporary increases in frequency. Our model is illustrated using a 10^8-word database from an online discussion group and a 10^11-word collection of digitized books. The model reveals a strong relation between changes in word dissemination and changes in frequency. Aside from their implications for short-term word frequency dynamics, these observations are potentially important for language evolution as new words must survive in the short term in order to survive in the long term.

 

Identifying trends in word frequency dynamics

Eduardo G. Altmann, Zakary L. Whichard, Adilson E. Motter

http://arxiv.org/abs/1302.3892


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Networked Knowledge and Combinatorial Creativity

Networked Knowledge and Combinatorial Creativity | Information, Complexity, Computation | Scoop.it
Why creativity is like LEGO, or what Richard Dawkins has to do with Susan Sontag and Gandhi.

In May, I had the pleasure of speaking at th

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Every recorded meteorite strike on Earth since 2,300 BCE mapped

Every recorded meteorite strike on Earth since 2,300 BCE mapped | Information, Complexity, Computation | Scoop.it
The meteorite that struck central Russia last week, which injured around 1,000 people as it broke apart over a section of the Ural Mountains and sent shockwaves across the ground below, was but one...

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I wonder what the distribution is, the high concentration areas are almost always at the centre.

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Noise enhances information transfer in hierarchical networks

Noise enhances information transfer in hierarchical networks | Information, Complexity, Computation | Scoop.it

We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

 

Noise enhances information transfer in hierarchical networks

Agnieszka Czaplicka, Janusz A. Holyst & Peter M. A. Sloot

Scientific Reports 3, Article number: 1223 http://dx.doi.org/10.1038/srep01223


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Joint CRM-Imperial College School and Workshop in Complex Systems

April 8 to 11, 2013 (school) April 12 to 13, 2013 (workshop) at the Centre de Recerca Matematica, Bellaterra, Barcelona and in the Institut d’Estudis Catalans, Barcelona. The structure of this school + workshop will be: 1) School Courses: 6 courses will be offered at the expense of leading experts. These courses will treat topics of great current importance and interest for young researchers, who will have the opportunity to penetrate into these topics and to raise his doubts to the experts. The courses are: - Dynamics of Complex Systems (intermittency, stability, etc.). Henrik J. Jensen, Imperial College London. - Critical Phenomena and Percolation Theory. Kim Christensen, Imperial College London. - Percolation in Complex Networks. Marian Boguna, Universitat de Barcelona - Non-Equilibrium Phase Transitions, Field Theory and Self-Organised Criticality. Gunnar Pruessner, Imperial College London, - Complex Networks and Hidden Metric Spaces: Internet, Metabolic Networks… M. Angeles Serrano, Universitat de Barcelona. - Multifractal Formalism: from models for turbulent flows to applications in ocean remote sensing. Antonio Turiel, Institut de Ciencies del Mar, Barcelona. 2) Problem-solving classes: directly related to the contents of the courses. 3) Plenary lecture, by Stefan Thurner, Medical University of Vienna 4) Contributed Talks at the workshop 5) Posters It is possible to attend the school or the workshop separately Important deadlines: March 8, 2013 (contributed talks and posters) March 18, 2013 (registration and payment) If you wish to submit a talk or a poster, please send the required information to Ms Nuria Hernandez (nhernandez@crm.cat) A website for this activity can be accessed through the following link: http://www.crm.cat/2013/ComplexSystems


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ComplexInsight's curator insight, February 12, 2013 12:01 PM

Wont be able to attend this one - but wish i could. Scooping in case its of interest to others.

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The Timing and Targeting of Treatment in Influenza Pandemics Influences the Emergence of Resistance in Structured Populations

The Timing and Targeting of Treatment in Influenza Pandemics Influences the Emergence of Resistance in Structured Populations | Information, Complexity, Computation | Scoop.it

Antiviral resistance in influenza is rampant and has the possibility of causing major morbidity and mortality. Previous models have identified treatment regimes to minimize total infections and keep resistance low. However, the bulk of these studies have ignored stochasticity and heterogeneous contact structures. Here we develop a network model of influenza transmission with treatment and resistance, and present both standard mean-field approximations as well as simulated dynamics. We find differences in the final epidemic sizes for identical transmission parameters (bistability) leading to different optimal treatment timing depending on the number initially infected. We also find, contrary to previous results, that treatment targeted by number of contacts per individual (node degree) gives rise to more resistance at lower levels of treatment than non-targeted treatment. Finally we highlight important differences between the two methods of analysis (mean-field versus stochastic simulations), and show where traditional mean-field approximations fail. Our results have important implications not only for the timing and distribution of influenza chemotherapy, but also for mathematical epidemiological modeling in general. Antiviral resistance in influenza may carry large consequences for pandemic mitigation efforts, and models ignoring contact heterogeneity and stochasticity may provide misleading policy recommendations.


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ComplexInsight's curator insight, February 12, 2013 12:19 PM

This is an important piece of research for disease modeling and stochastic simulations versus mean field approaches. If disease modeling or health systems are in your interest area this is a must read. Click on image or title to learn more.