We investigated different dense multirotor UAV traffic simulation scenarios in open 2D and 3D space, under realistic environments with the presence of sensor noise, communication delay, limited communication range, limited sensor update rate and finite inertia. We implemented two fundamental self-organized algorithms: one with constant direction and one with constant velocity preference to reach a desired target. We performed evolutionary optimization on both algorithms in five basic traffic scenarios and tested the optimized algorithms under different vehicle densities. We provide optimal algorithm and parameter selection criteria and compare the maximal flux and collision risk of each solution and situation. We found that i) different scenarios and densities require different algorithmic approaches, i.e., UAVs have to behave differently in sparse and dense environments or when they have common or different targets; ii) a slower-is-faster effect is implicitly present in our models, i.e., the maximal flux is achieved at densities where the average speed is far from maximal; iii) communication delay is the most severe destabilizing environmental condition that has a fundamental effect on performance and needs to be taken into account when designing algorithms to be used in real life.

 

Self-organized UAV Traffic in Realistic Environment

Csaba Virágh, Máté Nagy, Carlos Gershenson, Gábor Vásárhelyi

Source: arxiv.org

Ah, but isn’t all this wonder simply the product of the blind fumbling of Darwinian evolution, that mindless machine which takes random variation and sieves it by natural selection? Well, not quite. You don’t have to be a benighted creationist, nor even a believer in divine providence, to argue that Darwin’s astonishing theory doesn’t fully explain why nature is so marvelously, endlessly inventive. “Darwin’s theory surely is the most important intellectual achievement of his time, perhaps of all time,” says evolutionary biologist Andreas Wagner of the University of Zurich. “But the biggest mystery about evolution eluded his theory. And he couldn’t even get close to solving it.”

Source: nautil.us

For centuries, thinkers have considered whether and how climatic conditions—such as temperature, rainfall, and violent storms—influence the nature of societies and the performance of economies. A multidisciplinary renaissance of quantitative empirical research is illuminating important linkages in the coupled climate-human system. We highlight key methodological innovations and results describing effects of climate on health, economics, conflict, migration, and demographics. Because of persistent “adaptation gaps,” current climate conditions continue to play a substantial role in shaping modern society, and future climate changes will likely have additional impact. For example, we compute that temperature depresses current U.S. maize yields by ~48%, warming since 1980 elevated conflict risk in Africa by ~11%, and future warming may slow global economic growth rates by ~0.28 percentage points per year. In general, we estimate that the economic and social burden of current climates tends to be comparable in magnitude to the additional projected impact caused by future anthropogenic climate changes. Overall, findings from this literature point to climate as an important influence on the historical evolution of the global economy, they should inform how we respond to modern climatic conditions, and they can guide how we predict the consequences of future climate changes.

 

Social and economic impacts of climate
Tamma A. Carleton, Solomon M. Hsiang

Science  09 Sep 2016:
Vol. 353, Issue 6304,
DOI: 10.1126/science.aad9837

Source: science.sciencemag.org

Climate change, biodiversity loss, antibiotic resistance, and other global challenges pose major collective action problems: A group benefits from a certain action, but no individual has sufficient incentive to act alone. Formal institutions, e.g., laws and treaties, have helped address issues like ozone depletion, lead pollution, and acid rain. However, formal institutions are not always able to enforce collectively desirable outcomes. In such cases, informal institutions, such as social norms, can be important. If conditions are right, policy can support social norm changes, helping address even global problems. To judge when this is realistic, and what role policy can play, we discuss three crucial questions: Is a tipping point likely to exist, such that vicious cycles of socially damaging behavior can potentially be turned into virtuous ones? Can policy create tipping points where none exist? Can policy push the system past the tipping point?

 

Social norms as solutions
Karine Nyborg, John M. Anderies, Astrid Dannenberg, Therese Lindahl, Caroline Schill, Maja Schlüter, W. Neil Adger, Kenneth J. Arrow, Scott Barrett, Stephen Carpenter, F. Stuart Chapin III, Anne-Sophie Crépin, Gretchen Daily, Paul Ehrlich, Carl Folke, Wander Jager, Nils Kautsky, Simon A. Levin, Ole Jacob Madsen, Stephen Polasky, Marten Scheffer, Brian Walker, Elke U. Weber, James Wilen, Anastasios Xepapadeas, Aart de Zeeuw

Science  07 Oct 2016:
Vol. 354, Issue 6308, pp. 42-43
DOI: 10.1126/science.aaf8317

Source: science.sciencemag.org

The sensitivity (i.e. dynamic response) of complex networked systems has not been well understood, making difficult to predict whether new macroscopic dynamic behavior will emerge even if we know exactly how individual nodes behave and how they are coupled. Here we build a framework to quantify the sensitivity of complex networked system of coupled dynamic units. We characterize necessary and sufficient conditions for the emergence of new macroscopic dynamic behavior in the thermodynamic limit. We prove that these conditions are satisfied only for architectures with power-law degree distributions. Surprisingly, we find that highly connected nodes (i.e. hubs) only dominate the sensitivity of the network up to certain critical frequency.

 

Sensitivity of Complex Networks
Marco Tulio Angulo, Gabor Lippner, Yang-Yu Liu, Albert-László Barabási

Source: arxiv.org