Complexity at large

Authors

  • Carlos Gershenson


FILTERING A WEALTH OF DATA

The following news item is taken in part from the February 11, 2011 issue of Science titled “More Is Less: Signal Processing and the Data Deluge,” by Richard G. Baraniuk.

The data deluge is changing the operating environment of many sensing systems from data-poor to data-rich—so data-rich that we are in jeopardy of being overwhelmed. Managing and exploiting the data deluge require a reinvention of sensor system design and signal processing theory. The potential pay-offs are huge, as the resulting sensor systems will enable radically new information technologies and powerful new tools for scientific discovery.

A link to this article can be found at http://dx.doi.org/10.1126/science.1197448.

HAPPY PEOPLE LIVE LONGER

The following news item is taken in part from the February 4, 2011 issue of Science titled “Happy People Live Longer,” by Bruno S. Frey.

There is a longstanding idea that happiness causes people to live longer, healthier lives. However, convincing evidence that subjective well-being (SWB) (the more scholarly term for happiness) contributes to longevity and health has not been available. Recently, however, social psychologists Diener and Chan showed that many kinds of studies, using different methods, conclude that happiness has a positive causal effect on longevity and physiological health.

A link to this article can be found at http://dx.doi.org/10.1126/science.1201060.

PERTURBATIONS TO RESCUE ECOSYSTEMS

The following news item is taken in part from the January 25, 2011 issue of Nature Communications titled “Rescuing ecosystems from extinction cascades through compensatory perturbations,” by Sagar Sahasrabudhe and Adilson E. Motter.

Food-web perturbations stemming from climate change, overexploitation, invasive species, and habitat degradation often cause an initial loss of species that results in a cascade of secondary extinctions, posing considerable challenges to ecosystem conservation efforts. Here, we devise a systematic network-based approach to reduce the number of secondary extinctions using a predictive modeling framework. We show that the extinction of one species can often be compensated by the concurrent removal or population suppression of other specific species, a counterintuitive effect not previously tested in complex food webs.

A link to this article can be found at http://dx.doi.org/10.1038/ncomms1163.

NATURE-INSPIRED DISTRIBUTED ALGORITHM

The following news item is taken in part from the January 14, 2011 issue of Science titled “A Biological Solution to a Fundamental Distributed Computing Problem,” by Yehuda Afek, Noga Alon, Omer Barad, Eran Hornstein, Naama Barkai, and Ziv Bar-Joseph.

Computational and biological systems are often distributed so that processors (cells) jointly solve a task, without any of them receiving all inputs or observing all outputs. Maximal independent set (MIS) selection is a fundamental distributed computing procedure that seeks to elect a set of local leaders in a network. A variant of this problem is solved during the development of the fly's nervous system, when sensory organ precursor (SOP) cells are chosen. By studying SOP selection, we derived a fast algorithm for MIS selection (…)

A link to this article can be found at http://dx.doi.org/10.1126/science.1193210.

SCHEMA REDESCRIPTION IN CELLULAR AUTOMATA

The following news item is taken in part from the February 2, 2011 issue of arXiv titled “Schema Redescription in Cellular Automata: Revisiting Emergence in Complex Systems,” by Manuel Marques-Pita and Luis M. Rocha.

We present a method to eliminate redundancy in the transition tables of Boolean automata: schema redescription with two symbols. One symbol is used to capture redundancy of individual input variables, and another to capture permutability in sets of input variables: fully characterizing the canalization present in Boolean functions. Two-symbol schemata explain aspects of the behavior of automata networks that the characterization of their emergent patterns does not capture. (…) we demonstrate that it is more feasible to compare cellular automata via schema redescriptions of their rules, than by looking at their emergent behavior, leading us to question the tendency in complexity research to pay much more attention to emergent patterns than to local interactions.

A link to this article can be found at http://arXiv.org/abs/1102.1691.

SYSTEMS GENETICS

The following news item is taken in part from the February 25, 2011 issue of Science titled “Systems Genetics,” by Joseph H. Nadeau and Aimée M. Dudley.

Systems genetics seeks to understand this complexity by integrating the questions and methods of systems biology with those of genetics to solve the fundamental problem of interrelating genotype and phenotype in complex traits and disease.

A link to this article can be found at http://dx.doi.org/10.1126/science.1203869.

PERSPECTIVES OF THEORETICAL BIOLOGY

The following news item is taken in part from the May 7, 2011 issue of Journal of Theoretical Biology titled “The challenges and scope of theoretical biology,” by David C. Krakauer, James P. Collins, Douglas Erwin, Jessica C. Flack, Walter Fontana, Manfred D. Laubichler, Sonja J. Prohaska, Geoffrey B. West, and Peter F. Stadler.

(…) model building has proven to be very successful when it comes to explaining and predicting the behavior of particular biological systems. In this respect, biology resembles alternate model-rich frameworks, such as economics and engineering. In this article, we explore the prospects for general theories in biology, and suggest that these take inspiration not only from physics, but also from the information sciences. Future theoretical biology is likely to represent a hybrid of parsimonious reasoning and algorithmic or rule-based explanation.

A link to this article can be found at http://dx.doi.org/10.1016/j.jtbi.2011.01.051.

PREDICTING THE MARKET

The following news item is taken in part from the February 13, 2011 issue of arXiv titled “Predicting economic market crises using measures of collective panic,” by Dion Harmon, Marcus A. M. de Aguiar, David D. Chinellato, Dan Braha, Irving R. Epstein, and Yaneer Bar-Yam.

Predicting panic is of critical importance in many areas of human and animal behavior, notably in the context of economics. The recent financial crisis is a case in point. Panic may be due to a specific external threat, or self-generated nervousness. Here, we show that the recent economical crisis and earlier large single-day panics were preceded by extended periods of high levels of market mimicry—direct evidence of uncertainty and nervousness, and of the comparatively weak influence of external news. High levels of mimicry can be a quite general indicator of the potential for self-organized crises.

A link to this article can be found at http://arXiv.org/abs/1102.2620.

MODULARITY IN NETWORKS

The following news item is taken in part from the February 24, 2011 issue of arXiv titled “Robustness and modular structure in networks,” by James P. Bagrow, Sune Lehmann, and Yong-Yeol Ahn.

Many complex systems, from power grids and the internet, to the brain and society, can be modeled using modular networks. Modules, densely interconnected groups of elements, often overlap due to elements that belong to multiple modules. The elements and modules of these networks perform individual and collective tasks such as generating and consuming electrical load, transmitting data, or executing parallelized computations. We study the robustness of these systems to the failure of random elements. We show that it is possible for the modules themselves to become isolated or uncoupled (nonoverlapping) well before the network falls apart. When modular organization is critical to overall functionality, networks may be far more vulnerable than expected.

A link to this article can be found at http://arXiv.org/abs/1102.5085.

WHEN ARE CROWDS SMARTER THAN EXPERTS?

The following news item is taken in part from the March 3, 2011 issue of Nature titled “Collective behavior: When it pays to share decisions,” by Larissa Conradt.

|||Theory suggests that the accuracy of a decision often increases with the number of decision makers, a phenomenon exploited by betting agents, Internet search engines and stock markets. Fish also use this ‘wisdom of the crowd’ effect.

A link to this article can be found at http://dx.doi.org/10.1038/471040a.

ARE WE LIVING A MASS EXTINCTION?

The following news item is taken in part from the March 3, 2011 issue of Nature titled “Has the Earth's sixth mass extinction already arrived?,” by Anthony D. Barnosky, Nicholas Matzke, Susumu Tomiya, Guinevere O. U. Wogan, Brian Swartz, Tiago B. Quental, Charles Marshall, Jenny L. McGuire, Emily L. Lindsey, Kaitlin C. Maguire, Ben Mersey & Elizabeth A. Ferrer.

Palaeontologists characterize mass extinctions as times when the Earth loses more than three-quarters of its species in a geologically short interval, as has happened only five times in the past 540 million years or so. Biologists now suggest that a sixth mass extinction may be under way, given the known species losses over the past few centuries and millennia. Here we review how differences between fossil and modern data and the addition of recently available palaeontological information influence our understanding of the current extinction crisis. Our results confirm that current extinction rates are higher than would be expected from the fossil record, highlighting the need for effective conservation measures.

A link to this article can be found at http://dx.doi.org/10.1038/nature09678.

CORRELATION OF FITNESS AND INFORMATION INTEGRATION

The following news item is taken in part from the March 9, 2011 issue of arXiv titled “Integrated information increases with fitness in the simulated evolution of autonomous agents,” by Jeffrey Edlund, Nicolas Chaumont, Arend Hintze, Christof Koch, Giulio Tononi, and Christoph Adami.

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular as their functional complexity is not well-defined. Here we present several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent evolves over thousands of generations to solve a navigation task in a simple, simulated environment. (…) A correlation of measures of information integration (…) and fitness strongly suggests that these measures reflect the functional complexity of the agent, and that such measures can be used to quantify functional complexity even in the absence of fitness data.

A link to this article can be found at http://arXiv.org/abs/1103.1791.

DEGREE DISTRIBUTIONS OF BIPARTITE ECOLOGICAL NETWORKS

The following news item is taken in part from the March 3, 2011 issue of PLoS ONE titled “Biology, Methodology or Chance? The Degree Distributions of Bipartite Ecological Networks,” by Richard J. Williams.

The shape of a degree distribution, for example whether it follows an exponential or power-law form, is typically taken to be indicative of the processes structuring the network. The skewed degree distributions of bipartite mutualistic and antagonistic networks are usually assumed to show that ecological or co-evolutionary processes constrain the relative numbers of specialists and generalists in the network. I show that a simple null model based on the principle of maximum entropy cannot be rejected as a model for the degree distributions in most of the 115 bipartite ecological networks tested here.

A link to this article can be found at http://dx.doi.org/10.1371/journal.pone.0017645.

HAPPINESS IN SOCIAL NETWORKS

The following news item is taken in part from the March 3, 2011 issue of arXiv titled “Happiness is assortative in online social networks,” by Johan Bollen, Bruno Goncalves, Guangchen Ruan, Huina Mao.

Social networks tend to disproportionally favor connections between individuals with either similar or dissimilar characteristics. This propensity, referred to as assortative mixing or homophily, is expressed as the correlation between attribute values of nearest neighbour vertices in a graph. Recent results indicate that beyond demographic features such as age, sex and race, even psychological states such as “loneliness” can be assortative in a social network. In spite of the increasing societal importance of online social networks it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that general happiness or SWB of Twitter users, as measured from a 6-month record of their individual tweets, is indeed assortative across the Twitter social network. (…)

A link to this article can be found at http://arXiv.org/abs/1103.0784.

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