Is it Rodney King and the Kent State massacre all over again?
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The epic battle against coronavirus misinformation and conspiracy
By studying the sources and spread of false information about
COVID-19, researchers hope to understand where such information
comes from, how it grows and — they hope — how to elevate facts
over falsehood. It’s a battle that can’t be won completely,
researchers agree — it’s not possible to stop people from
spreading ill-founded rumours. But in the language of
epidemiology, the hope is to come up with effective strategies to
‘flatten the curve’ of the infodemic, so that bad information
can’t spread as far and as fast.
The information theory of individuality
David Krakauer, Nils Bertschinger, Eckehard Olbrich, Jessica C.
Flack & Nihat Ay
Theory in Biosciences volume 139, pages209–223(2020)
Despite the near universal assumption of individuality in biology,
there is little agreement about what individuals are and few
rigorous quantitative methods for their identification. Here, we
propose that individuals are aggregates that preserve a measure of
temporal integrity, i.e., “propagate” information from their past
into their futures. We formalize this idea using information
theory and graphical models. This mathematical formulation yields
three principled and distinct forms of individuality—an
organismal, a colonial, and a driven form—each of which varies in
the degree of environmental dependence and inherited information.
This approach can be thought of as a Gestalt approach to evolution
where selection makes figure-ground (agent–environment)
distinctions using suitable information-theoretic lenses. A
benefit of the approach is that it expands the scope of allowable
individuals to include adaptive aggregations in systems that are
multi-scale, highly distributed, and do not
necessarily have physical boundaries such as cell walls or clonal
somatic tissue. Such individuals might be visible to selection but
hard to detect by observers without suitable measurement
principles. The information theory of individuality allows for the
identification of individuals at all levels of organization from
molecular to cultural and provides a basis for testing assumptions
about the natural scales of a system and argues for the importance
of uncertainty reduction through coarse-graining in adaptive
Complex Systems: A Communication Networks Perspective Towards 6G
Charalampos Sergiou ; Marios Lestas ; Pavlos Antoniou ; Christos
Liaskos ; Andreas Pitsillides
IEEE Access ( Volume: 8 )
Over the last few years, the analysis and modeling of networks as
well as the analysis and modeling of networked dynamical systems,
has attracted considerable interdisciplinary interest, especially
using the complex systems theory. These efforts are driven by the
fact that systems, as diverse as genetic networks or the Internet
can be effectively described as complex networks. Contrary,
despite the unprecedented evolution of technology, basic issues
and fundamental principles related to the structural and
evolutionary properties of communication networks still remain
largely unaddressed. The situation is even more complicated when
we attempt to model the mobile communication networks and
especially the 5th generation (5G) and eventually the forthcoming
6th generation (6G). In this work, we attempt to review basic
models of complex networks from a communication networks
perspective, focusing on their structural and evolutionary
properties. Based on this review we aim to reveal the models of
complex networks, that may apply when modeling the 5G and 6G
mobile communication networks. Furthermore, we expect to encourage
the collaboration between complex systems and networking theorists
toward meeting the challenging demands of 5G networks and beyond.
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.
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