A new tool for multilayer networks

Sophisticated network analysis means finding relationships that often aren’t easy to see. A new algorithm from an interdisciplinary team at SFI identifies relationships not only within individual layers, but also across multiple layers.

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What algae can tell us about political strategy

Cells compete for nutrients. Political campaigns compete for voters. According to new research published in Nature Scientific Reports, general principles may begin to explain how differing strategies play out where groups compete for resources.

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Enroll now for the Dynamics and Chaos MOOC with David Feldman

SFI's free online course, Introduction to Dynamical Systems and Chaos with College of the Atlantic professor David Feldman, begins September 4. Topics to be covered include: phase space, bifurcations, chaos, the butterfly effect, strange attractors, and pattern formation.

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What algorithms can’t tell us about community detection

Groups of interconnected nodes, called “communities” or “modules,” represent real-world relationships like friend groups on Facebook, businesses in a supply chain. A new paper addresses the challenge of identifying whether, and ultimately where, these structures exist within a mass of data.

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Hayek’s market algorithm is not the road to laissez faire

In a fresh look at 20th-century philosopher-economist Friedrich Hayek, three authors note how the Nobel laureate’s work exemplifies complexity economics. They also show how his political support of laissez faire economic policies needn’t necessarily follow.

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How neurons use crowdsourcing to make decisions

How we make decisions— or, rather, how neurons make decisions for us, is the subject of new research published in Frontiers in Neuroscience. In the study, Bryan Daniels, Jessica Flack, and David Krakauer uncover a two-phase collective decision-making pattern which may suggest a general principle of collective computation.

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