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BIG HISTORY

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the 2(1) issue of Cliodynamics titled “An Inquiry into History, Big History, and Metahistory,” by, David C. Krakauer, John Gaddis, and Kenneth Pomeranz.

What is history anyway? Most people would say it is what happened in the past, but how far back does the past extend? To the first written sources? To what other forms of evidence reveal about preliterate civilizations? What does that term mean—an empire, a nation, a city, a village, a family, and a lonely hermit somewhere? Why stop with people: history also should not comprise the environment in which they exist, and if so on what scale and how far back? And, as long as we are headed in that direction, why stop with the earth and the solar system? Why not go all the way back to the Big Bang itself?

A link to this article can be found at http://escholarship.org/uc/item/7xk1n3wb.

COMPUTATIONAL SOCIAL SCIENCE

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the March 31, 2011 issue of Nature titled “Social science: Web of war,” by Sharon Weinberger.

Comer and other officials are placing their bets on a new generation of computer models that try to predict how groups behave, and how that behavior can be changed. This work goes under a variety of names, including “human dynamics” and “computational social science.” It represents a melding of research fields from social-network analysis to political forecasting and complexity science.

A link to this article can be found at http://www.nature.com/news/2011/110330/full/471566a.html.

PROPAGATION OF CASCADES IN COMPLEX NETWORKS

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the March 22, 2011 issue of arXiv titled “Propagation of Cascades in Complex Networks: From Supply Chains to Food Webs,” by Reginald D. Smith.

A general theory of top-down cascades in complex networks is described, and it explains two similar types of perturbation amplifications in the complex networks of business supply chains (the “bullwhip effect”) and ecological food webs (trophic cascades). The dependence of the strength of the effects on the interaction strength and covariance in the dynamics as well as the graph structure allows both explanation and prediction of widely recognized effects in each type of system.

A link to this article can be found at http://arXiv.org/abs/1103.4983.

THE WORLD'S COMPUTATIONAL CAPACITIES

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the April 1, 2011 issue of Science titled “The World's Technological Capacity to Store, Communicate, and Compute Information,” by Martin Hilbert and Priscila López.

We estimated the world's technological capacity to store, communicate, and compute information, tracking 60 analog and digital technologies during the period from 1986 to 2007. In 2007, humankind was able to store 2.9 × 1020 optimally compressed bytes, communicate almost 2 × 1021 bytes, and carry out 6.4 × 1018 instructions per second on general-purpose computers. General-purpose computing capacity grew at an annual rate of 58%. The world's capacity for bidirectional telecommunication grew at 28% per year, closely followed by the increase in globally stored information (23%).

A link to this article can be found at http://dx.doi.org/10.1126/science.1200970.

THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the February, 2011 issue of SFI Working Papers titled “The Evolution and Structure of Sustainability Science,” by Luis M.A. Bettencourt and Jasleen Kaur.

The concepts of sustainable development have experienced extraordinary success since their advent in the 1980s. They are now an integral part of the agenda of governments and corporations, and their goals have become central to the mission of research laboratories and universities worldwide. However, it remains unclear how far the field has progressed as a scientific discipline, especially given its ambitious agenda of integrating theory, applied science and policy, making it relevant for development globally and generating a new interdisciplinary synthesis across fields as diverse as ecology, the social sciences and engineering. (…) We show that sustainability science has been growing explosively since the late 1980s (…)

EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the April 20, 2011 issue of arXiv titled “Emergent Criticality Through Adaptive Information Processing in Boolean Networks,” by Alireza Goudarzi, Christof Teuscher, Natali Gulbahce, and Thimo Rohlf.

We study information processing in populations of Boolean networks with evolving connectivity and systematically explore the interplay between the learning capability, robustness, the network topology, and the task complexity. We solve a long-standing open question and find computationally that, for large system sizes N, adaptive information processing drives the networks to a critical connectivity Kc = 2. For finite size networks, the connectivity approaches the critical value with a power-law of the system size N. (…)

A link to this article can be found at http://arXiv.org/abs/1104.4141.

STABILITY OF THE WORLD TRADE WEB

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 18, 2011 issue of arXiv titled “Stability of the World Trade Web over Time—An Extinction Analysis,” by Nick Foti, Scott Pauls, and Daniel N. Rockmore.

The World Trade Web (WTW) is a weighted network, whose nodes correspond to countries with edge weights reflecting the value of imports and/or exports between countries. In this paper, we introduce to this macroeconomic system the notion of extinction analysis, a technique often used in the analysis of ecosystems, for the purposes of investigating the robustness of this network. In particular, we subject the WTW to a principled set of in silico "knockout experiments," akin to those carried out in the investigation of food webs, but suitably adapted to this macroeconomic network. Broadly, our experiments show that over time the WTW moves to a "robust yet fragile" configuration, where it is robust under random attacks but fragile under targeted attack. (…)

A link to this article can be found at http://arXiv.org/abs/1104.4380.

EVOLUTIONARY LITERATURE

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 6, 2011 issue of Science titled “Red in Tooth and Claw Among the Literati,” by Sam Kean.

Some literary scholars have begun incorporating neuroscience, cognitive science, anthropology, and—most prominently and controversially—evolutionary psychology into their work. Their work explores how evolution might have shaped aspects of the literature, the potential adaptive benefits of storytelling for our Pleistocene ancestors, and the mystery of why humans spend so much time immersed in it. Evolution provides a framework for understanding human behavior and evolutionary psychology explores the origins of mental phenomena and can bridge evolutionary biology and the humanities.

A link to this article can be found at http://dx.doi.org/10.1126/science.332.6030.654.

RECONSTRUCTING THE PAST OF NETWORKS

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the April 14, 2011 issue of PLoS Comput Biol titled “Network Archeology: Uncovering Ancient Networks from Present-Day Interactions,” by Saket Navlakha and Carl Kingsford.

Many questions about present-day interaction networks could be answered by tracking how the network changed over time. We present a suite of algorithms to uncover an approximate node-by-node and edge-by-edge history of changes of a network when given only a present-day network and a plausible growth model by which it evolved.

A link to this article can be found at http://dx.doi.org/10.1371/journal.pcbi.1001119.

CONTROLLING NETWORKS

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 11, 2011 issue of Nature titled “Controllability of complex networks,” by Yang-Yu Liu, Jean-Jacques Slotine, and Albert-László Barabási.

The ultimate proof of our understanding of natural or technological systems is reflected in our ability to control them. Although control theory offers mathematical tools for steering engineered and natural systems toward a desired state, a framework to control complex self-organized systems is lacking. Here, we develop analytical tools to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes with time-dependent control that can guide the system's entire dynamics. We apply these tools to several real networks, finding that the number of driver nodes is determined mainly by the network's degree distribution. We show that sparse inhomogeneous networks, which emerge in many real complex systems, are the most difficult to control, but that dense and homogeneous networks can be controlled using a few driver nodes. Counterintuitively, we find that in both model and real systems the driver nodes tend to avoid the high-degree nodes.

A link to this article can be found at http://dx.doi.org/10.1038/nature10011.

HOW STRUCTURE DETERMINES CORRELATIONS

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 19, 2011 issue of PLoS Comput Biol titled “How Structure Determines Correlations in Neuronal Networks,” by Volker Pernice, Benjamin Staude, Stefano Cardanobile, and Stefan Rotter.

Many biological systems have been described as networks, whose complex properties influence the behavior of the system. Correlations of activity in such networks are of interest in a variety of fields, from gene-regulatory networks to neuroscience. (…) We present a detailed explanation of how recurrent connectivity induces correlations in local neural networks and how structural features affect their size and distribution. We examine under which conditions network characteristics like distance-dependent connectivity, hubs or patches markedly influence correlations and population signals.

A link to this article can be found at http://dx.doi.org/10.1371/journal.pcbi.1002059.

THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 13, 2011 issue of arXiv titled “The Implications of Interactions for Science and Philosophy,” by Carlos Gershenson.

Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions, which reductionism neglects, are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, nonmaterialism, nonpredictability, non-Platonism, and nonnihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world but also can help to solve many open scientific, philosophical, and social problems caused by implications of reductionism.

A link to this article can be found at http://arXiv.org/abs/1105.2827.

LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 20, 2011 issue of PLoS ONE titled “Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies,” by Benjamin Blonder and Anna Dornhaus.

Using thousands of time-stamped interactions between uniquely marked ants in four colonies of a range of sizes, we demonstrate that observed maximum rates of information flow are always slower than predicted and are constrained by regulation of individual mobility and contact rate. By accounting for the ordering and timing of interactions, we can resolve important difficulties with network sampling frequency and duration, enabling a broader understanding of interaction network functioning across systems and scales.

A link to this article can be found at http://dx.doi.org/10.1371/journal.pone.0020298.

SELF-ORGANIZED DISCRIMINATION OF RESOURCES

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 18, 2011 issue of PLoS ONE titled “Self-Organized Discrimination of Resources,” by Alexandre Campo, Simon Garnier, Olivier Dédriche, Mouhcine Zekkri, and Marco Dorigo.

When selecting a resource to exploit, an insect colony must take into account at least two constraints (…) Following recent results on cockroaches and ants, we introduce here a behavioral mechanism that satisfies these two constraints. Individuals simply modulate their probability to switch to another resource as a function of the local density of conspecifics locally detected. As a result, the individuals gather at the smallest resource that can host the whole group.

A link to this article can be found at http://dx.doi.org/10.1371/journal.pone.0019888.

GROWTH AND OPTIMALITY IN NETWORK EVOLUTION

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS

The following news item is taken in part from the May 13, 2011 issue of arXiv titled “Growth and Optimality in Network Evolution,” by Markus Brede.

In this paper, we investigate networks, whose evolution is governed by the interaction of a random assembly process and an optimization process. In the first process, new nodes are added one at a time and form connections to randomly selected old nodes. In between node additions, the network is rewired to minimize its pathlength. For timescales, at which neither the assembly nor the optimization processes are dominant, we find a rich variety of complex networks with power-law tails in the degree distributions. These networks also exhibit nontrivial clustering, a hierarchical organization, and interesting degree mixing patterns.

A link to this article can be found at http://arXiv.org/abs/1105.2614.

CONFERENCE ANNOUNCEMENTS

  1. Top of page
  2. BIG HISTORY
  3. COMPUTATIONAL SOCIAL SCIENCE
  4. PROPAGATION OF CASCADES IN COMPLEX NETWORKS
  5. THE WORLD'S COMPUTATIONAL CAPACITIES
  6. THE EVOLUTION AND STRUCTURE OF SUSTAINABILITY SCIENCE
  7. EMERGENT CRITICALITY THROUGH ADAPTIVE INFORMATION PROCESSING
  8. STABILITY OF THE WORLD TRADE WEB
  9. EVOLUTIONARY LITERATURE
  10. RECONSTRUCTING THE PAST OF NETWORKS
  11. CONTROLLING NETWORKS
  12. HOW STRUCTURE DETERMINES CORRELATIONS
  13. THE IMPLICATIONS OF INTERACTIONS FOR SCIENCE AND PHILOSOPHY
  14. LIMITATIONS TO INFORMATION FLOW IN ANT COLONIES
  15. SELF-ORGANIZED DISCRIMINATION OF RESOURCES
  16. GROWTH AND OPTIMALITY IN NETWORK EVOLUTION
  17. CONFERENCE ANNOUNCEMENTS