Feed aggregator

This event, hosted by the Institute of Quantitative Social Science at Harvard University and organized by the Center of Complex Network Research at Northeastern University on June 17th, brings together social scientists, computer scientists, economists, physicists and mathematicians to discuss the quantitative laws and patterns behind success. 

 

Speakers

Pierre Azoulay James A. Evans
Santo Fortunato Gautam Mukunda
Alexander M. Petersen Camille Sweeney
Arnout van de Rijt Brian Uzzi
Christoph Riedl Nicola Perra
Duncan Watts Chaoming Song

 

http://www.barabasilab.com/success/

See it on Scoop.it, via CxConferences

It is conventional in labor economics to treat all workers who are seeking new jobs as belonging to a labor pool, and all firms that have job vacancies as an employer pool, and then match workers to jobs. Here we develop a new approach to study labor and firm dynamics. By combining the emerging science of networks with newly available employment micro-data, comprehensive at the level of whole countries, we are able to broadly characterize the process through which workers move between firms. Specifically, for each firm in an economy as a node in a graph, we draw edges between firms if a worker has migrated between them, possibly with a spell of unemployment in between. An economy's overall graph of firm-worker interactions is an object we call the labor flow network (LFN). This is the first study that characterizes a LFN for an entire economy. We explore the properties of this network, including its topology, its community structure, and its relationship to economic variables. It is shown that LFNs can be useful in identifying firms with high growth potential. We relate LFNs to other notions of high performance firms. Specifically, it is shown that fewer than 10% of firms account for nearly 90% of all employment growth. We conclude with a model in which empirically-salient LFNs emerge from the interaction of heterogeneous adaptive agents in a decentralized labor market.

 

Guerrero OA, Axtell RL (2013) Employment Growth through Labor Flow Networks. PLoS ONE 8(5): e60808. http://dx.doi.org/10.1371/journal.pone.0060808

See it on Scoop.it, via Papers

Flies are among the most agile flying creatures on Earth. To mimic this aerial prowess in a similarly sized robot requires tiny, high-efficiency mechanical components that pose miniaturization challenges governed by force-scaling laws, suggesting unconventional solutions for propulsion, actuation, and manufacturing. To this end, we developed high-power-density piezoelectric flight muscles and a manufacturing methodology capable of rapidly prototyping articulated, flexure-based sub-millimeter mechanisms. We built an 80-milligram, insect-scale, flapping-wing robot modeled loosely on the morphology of flies. Using a modular approach to flight control that relies on limited information about the robot’s dynamics, we demonstrated tethered but unconstrained stable hovering and basic controlled flight maneuvers. The result validates a sufficient suite of innovations for achieving artificial, insect-like flight.

 

Controlled Flight of a Biologically Inspired, Insect-Scale Robot
Kevin Y. Ma, Pakpong Chirarattananon, Sawyer B. Fuller, Robert J. Wood

Science 3 May 2013:
Vol. 340 no. 6132 pp. 603-607
http://dx.doi.org/10.1126/science.1231806

See it on Scoop.it, via Papers

Logic gates evoke images of circuit boards, but cells are arguably equally good in relying on logic computations. A classic example is the Lac operon, which activates itself upon the condition “lactose AND NOT glucose” (1). In recent years, there have been multiple reports on rationally designed, genetically encoded logic gates and circuits in living cells (2). Just like the Lac operon, these gates receive two or more molecular signals (inputs) and generate a product (output) whose level is logically linked to the inputs. Sixteen different logic connections are possible with two inputs and one output, but many of these operations have remained refractory to rational design. The trickiest of these gates usually make general statements about the inputs without referring to their exact values, such as “both inputs are the same” (an XNOR gate) or “two inputs are different” (an XOR gate). Two studies, one on page 599 of this issue by Bonnet et al. (3) and one by Siuti et al. (4), describe approaches that produce any of the 16 gates, including the notorious XNOR and XOR, in a compact manner by making relatively minor tweaks to the gates' genetic building blocks.

 

Recombinatorial Logic
Yaakov Benenson

Science 3 May 2013:
Vol. 340 no. 6132 pp. 554-555
http://dx.doi.org/10.1126/science.1237738

See it on Scoop.it, via Papers

The cosmological natural selection (CNS) hypothesis holds that the fundamental constants of nature have been fine-tuned by an evolutionary process in which universes produce daughter universes via the formation of black holes. Here, we formulate the CNS hypothesis using standard mathematical tools of evolutionary biology. Specifically, we capture the dynamics of CNS using Price's equation, and we capture the adaptive purpose of the universe using an optimization program. We establish mathematical correspondences between the dynamics and optimization formalisms, confirming that CNS acts according to a formal design objective, with successive generations of universes appearing designed to produce black holes.

 

Cosmological natural selection and the purpose of the universe

Andy Gardner, Joseph P. Conlon

Complexity, Early View

http://dx.doi.org/10.1002/cplx.21446

See it on Scoop.it, via Papers

The study of scientific models has become an active and important focus in history and philosophy of science, and to a lesser extent in sociology of science. Such attention acknowledges that models are central to scientific practice and that they are distinct from both theory and data, but there is a growing realization that modeling practices differ between and within disciplines. This special issue uses this realization to extend the discussion on models into new areas and different uses in the human and social sciences.

 

Modeling Practices in the Social and Human Sciences. An Interdisciplinary Exchange
Mary S. Morgan and Till Grüne-Yanoff
Perspectives on Science Summer 2013, Vol. 21, No. 2, Summer 2013: 143-156.

http://dx.doi.org/10.1162/POSC_a_00089

See it on Scoop.it, via Papers

In socially foraging species resource information can be shared between individuals, increasing foraging success. In ant colonies, nestmate recruitment allows high exploitation rates at known resources however, to maximise foraging efficiency this must be balanced with searching for new resources.

See it on Scoop.it, via Papers

Task-partitioning is an important organisational principle in insect colonies and is thought to increase colony efficiency. In task-partitioning, tasks such as the collection of resources are divided into subtasks in which the material is passed from one worker to another. We used an agent-based simulation model to explore how non-random interactions during task-partitioning with direct transfer affect colony work efficiency.

See it on Scoop.it, via Papers

This paper proposes a control framework for biological systems subject to dynamics that exhibit adaptive behavior under evolutionary pressures. The control framework was formulated based on evolutionary game based modeling, which integrates both the internal dynamics and the population dynamics.

See it on Scoop.it, via Papers

The fixation of cooperation among unrelated individuals is one of the fundamental problems in biology and social sciences. It is investigated by means of public goods games, the generalization of the prisoner's dilemma to more than two players. In compulsory public goods games, defect is the dominant strategy, while voluntary participation overcomes the social dilemma by allowing a cyclic coexistence of cooperators, defectors, and non-participants. [...] a milder punishing mechanism, where defectors only risk a fixed penalty per round—as in many real situations—and the cost of punishment is shared among the punishers. The payoffs for the four strategies—cooperate, defect, abstain, and cooperate-&-punish—are derived and the corresponding replicator dynamics analyzed in full detail.

See it on Scoop.it, via Papers

The extended mind hypothesis has stimulated much interest in cognitive science. However, its core claim, i.e. that the process of cognition can extend beyond the brain via the body and into the environment, has been heavily criticized. A prominent critique of this claim holds that when some part of the world is coupled to a cognitive system this does not necessarily entail that the part is also constitutive of that cognitive system. This critique is known as the "coupling-constitution fallacy". In this paper we respond to this reductionist challenge by using an evolutionary robotics approach to create a minimal model of two acoustically coupled agents. We demonstrate how the interaction process as a whole has properties that cannot be reduced to the contributions of the isolated agents. We also show that the neural dynamics of the coupled agents has formal properties that are inherently impossible for those neural networks in isolation. By keeping the complexity of the model to an absolute minimum, we are able to illustrate how the coupling-constitution fallacy is in fact based on an inadequate understanding of the constitutive role of nonlinear interactions in dynamical systems theory.


The Dynamically Extended Mind -- A Minimal Modeling Case Study
Tom Froese, Carlos Gershenson, David A. Rosenblueth
Accepted in Congress on Evolutionary Computation IEEE CEC 2013, Evolutionary Robotics track
http://arxiv.org/abs/1305.1958

School on Nonlinearity and Stochasticity in Emergent Phenomena

July 29th - August 2nd, 2013

Centro Internacional de Ciencias A.C. Cuernavaca, Mexico.

http://www.cicc.unam.mx/activities/2013/snlsep/index.html

 

Lecturers
Rafael Barrio Instituto de Física, UNAM. Mexico
Carlos Gershenson Instituto de Investigación en Matemáticas Aplicadas y Sistemas, UNAM. Mexico
Holger Henning Harvard University. USA
David Hochberg Centro de Astrobiología, CSIC/INTA. Spain
Henrik Jensen Imperial College London. UK
María Elena Lárraga Instituto de Ingeniería, UNAM. Mexico

See it on Scoop.it, via CxConferences

In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.

 

A review on agent-based technology for traffic and transportation
Ana L. C. Bazzan and Franziska Klügl

The Knowledge Engineering Review

http://dx.doi.org/10.1017/S0269888913000118

See it on Scoop.it, via Papers

In this deeply researched and piercingly intelligent book, physicist Mark Buchanan shows how a simple feedback loop can lead to major consequences, the kind predictable by mathematical models but hard for most people to anticipate. From his unique perspective, Buchanan argues that our basic assumptions about economic markets--that they are for the most part stable, with occasional interruptions--are simply wrong. Markets really act more like the weather: a brief heat wave can become a massive storm in a matter of a few days, or even hours.

The Physics of Finance reimagines the basics of how economics, with consequences that affect everyone.

 

 

See it on Scoop.it, via CxBooks

What is your favorite deep, elegant, or beautiful explanation?

This is the question John Brockman, publisher of Edge.org, posed to the world's most influential minds. Flowing from the horizons of physics, economics, psychology, neuroscience, and more, This Explains Everything presents 150 of the most surprising and brilliant theories of the way of our minds, societies, and universe work.

 

 

See it on Scoop.it, via CxBooks

In Systematicity, Paul Hoyningen-Huene answers the question "What is science?" by proposing that scientific knowledge is primarily distinguished from other forms of knowledge, especially everyday knowledge, by being more systematic. "Science" is here understood in the broadest possible sense, encompassing not only the natural sciences but also mathematics, the social sciences, and the humanities. The author develops his thesis in nine dimensions in which it is claimed that science is more systematic than other forms of knowledge: regarding descriptions, explanations, predictions, the defense of knowledge claims, critical discourse, epistemic connectedness, an ideal of completeness, knowledge generation, and the representation of knowledge. He compares his view with positions on the question held by philosophers from Aristotle to Nicholas Rescher. The book concludes with an exploration of some consequences of Hoyningen-Huene's view concerning the genesis and dynamics of science, the relationship of science and common sense, normative implications of the thesis, and the demarcation criterion between science and pseudo-science.

 

 

See it on Scoop.it, via CxBooks

Musician and naturalist Bernie Krause is one of the world's leading experts in natural sound, and he's spent his life discovering and recording nature's rich chorus. Searching far beyond our modern world's honking horns and buzzing machinery, he has sought out the truly wild places that remain, where natural soundscapes exist virtually unchanged from when the earliest humans first inhabited the earth.

Krause shares fascinating insight into how deeply animals rely on their aural habitat to survive and the damaging effects of extraneous noise on the delicate balance between predator and prey. But natural soundscapes aren't vital only to the animal kingdom; Krause explores how the myriad voices and rhythms of the natural world formed a basis from which our own musical expression emerged.

From snapping shrimp, popping viruses, and the songs of humpback whales-whose voices, if unimpeded, could circle the earth in hours-to cracking glaciers, bubbling streams, and the roar of intense storms; from melody-singing birds to the organlike drone of wind blowing over reeds, the sounds Krause has experienced and describes are like no others. And from recording jaguars at night in the Amazon rain forest to encountering mountain gorillas in Africa's Virunga Mountains, Krause offers an intense and intensely personal narrative of the planet's deep and connected natural sounds and rhythm.

The Great Animal Orchestra is the story of one man's pursuit of natural music in its purest form, and an impassioned case for the conservation of one of our most overlooked natural resources-the music of the wild.

 

 

See it on Scoop.it, via CxBooks

See it on Scoop.it, via Talks

Starting in the 19th century (...) and culminating with a 1963 paper by MIT meteorologist Edward Lorenz (...), a series of developments revealed that the notion of deterministic predictability, although appealingly intuitive, is in practice false for most systems. Small uncertainties in an initial state can indeed become large errors in a final one. Even simple systems for which all forces are known can behave unpredictably. Determinism, surprisingly enough, does not preclude chaos.

 

Chaos at fifty
Adilson E. Motter and David K. Campbell
Physics Today / Volume 66 / Issue 5, May 2013, page 27

http://dx.doi.org/10.1063/PT.3.1977

See it on Scoop.it, via Papers

Why did this interest and work in complexity not lead to major changes in management practices? There are, I think, a few major reasons that it didn't — and that also suggest that the overdue change might now finally take place.

 

Why Managers Haven't Embraced Complexity
by Richard Straub

http://blogs.hbr.org/cs/2013/05/why_managers_havent_embraced_c.html

See it on Scoop.it, via Papers