Month: October 2020

How Humans Judge Machines

How Humans Judge Machines is a peer-reviewed book comparing people’s reactions to human and machine actions. Through dozens of experiments, it brings us closer to understanding when people judge humans and machines differently, and why.

Source: www.judgingmachines.com

Capitalism After the Pandemic

Mariana Mazzucato

Foreign Affairs

 

After the 2008 financial crisis, governments across the world injected over $3 trillion into the financial system. The goal was to unfreeze credit markets and get the global economy working again. But instead of supporting the real economy—the part that involves the production of actual goods and services—the bulk of the aid ended up in the financial sector. Governments bailed out the big investment banks that had directly contributed to the crisis, and when the economy got going again, it was those companies that reaped the rewards of the recovery. Taxpayers, for their part, were left with a global economy that was just as broken, unequal, and carbon-intensive as before. “Never let a good crisis go to waste,” goes a popular policymaking maxim. But that is exactly what happened.

Source: www.foreignaffairs.com

CCS2018 Book of Abstracts

This is the book of Abstracts from the 2018 Conference on Complex Systems held in Thessaloniki, Greece, 23-28 September, 2018.

 

 
With this DOI reference any abstract in the CCS2018 Conference can be referenced in other future publications, and easily located as a citation by any other scientists. 
 
It is planned for CCS2020 to also publish the Book of Abstracts in the same way.
 
In order for your abstract to be included please note that it must conform exactly with the instructions as given in the CCS2020 Website.  

Source: zenodo.org

Visualization of dynamic structure in flocking behavior

Daichi Saito, Norihiro Maruyama, Yasuhiro Hashimoto & Takashi Ikegami
Artificial Life and Robotics (2020)

 

The flock structures produced by individuals, e.g., animals, self-organize and change their complexity over time. Although flock structures are often characterized by the spatial alignment of each element, this study focuses on their dynamic and hierarchical nature, temporal variations, and meta-structures. In hierarchical systems, sometimes, the upper structure is unchanged, whereas the lower components change constantly over time. Current clustering methods aim to capture the static and mono-layer features of complex patterning. To detect and track dynamic and hierarchical objects, a new clustering technique is required. Hence, in this study, we improve the generative topographic mapping (GTM) method to visualize such dynamic hierarchical structures as they continuously change over time. Using examples from our recent studies on the large-scale Boids model, we confirm that the newly developed method can capture the complex flocking objects as well as track the merging and collapsing events of objects.

Source: link.springer.com