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Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence
IEEE Access
Volume 3, 2015, Article number 7217798, Pages 1512-1530
Open Access
Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article)
Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc
a Department of Information Engineering, University of Padua, Padua, Italy
b Department of General Psychology, University of Padua, Padua, Italy
c IRCCS San Camillo Foundation, Venice-Lido, Italy
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Abstract
In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network
Computers from plants we never made. Speculations
We discuss possible designs and prototypes of computing systems that could be
based on morphological development of roots, interaction of roots, and analog
electrical computation with plants, and plant-derived electronic components. In
morphological plant processors data are represented by initial configuration of
roots and configurations of sources of attractants and repellents; results of
computation are represented by topology of the roots' network. Computation is
implemented by the roots following gradients of attractants and repellents, as
well as interacting with each other. Problems solvable by plant roots, in
principle, include shortest-path, minimum spanning tree, Voronoi diagram,
-shapes, convex subdivision of concave polygons. Electrical properties
of plants can be modified by loading the plants with functional nanoparticles
or coating parts of plants of conductive polymers. Thus, we are in position to
make living variable resistors, capacitors, operational amplifiers,
multipliers, potentiometers and fixed-function generators. The electrically
modified plants can implement summation, integration with respect to time,
inversion, multiplication, exponentiation, logarithm, division. Mathematical
and engineering problems to be solved can be represented in plant root networks
of resistive or reaction elements. Developments in plant-based computing
architectures will trigger emergence of a unique community of biologists,
electronic engineering and computer scientists working together to produce
living electronic devices which future green computers will be made of.Comment: The chapter will be published in "Inspired by Nature. Computing
inspired by physics, chemistry and biology. Essays presented to Julian Miller
on the occasion of his 60th birthday", Editors: Susan Stepney and Andrew
Adamatzky (Springer, 2017
Mathematics and Morphogenesis of the City: A Geometrical Approach
Cities are living organisms. They are out of equilibrium, open systems that
never stop developing and sometimes die. The local geography can be compared to
a shell constraining its development. In brief, a city's current layout is a
step in a running morphogenesis process. Thus cities display a huge diversity
of shapes and none of traditional models from random graphs, complex networks
theory or stochastic geometry takes into account geometrical, functional and
dynamical aspects of a city in the same framework. We present here a global
mathematical model dedicated to cities that permits describing, manipulating
and explaining cities' overall shape and layout of their street systems. This
street-based framework conciliates the topological and geometrical sides of the
problem. From the static analysis of several French towns (topology of first
and second order, anisotropy, streets scaling) we make the hypothesis that the
development of a city follows a logic of division / extension of space. We
propose a dynamical model that mimics this logic and which from simple general
rules and a few parameters succeeds in generating a large diversity of cities
and in reproducing the general features the static analysis has pointed out.Comment: 13 pages, 13 figure
The doctoral research abstracts. Vol:11 2017 / Institute of Graduate Studies, UiTM
Foreword:
Congratulation to IGS on the continuous effort to publish the 11th issue of the Doctoral Research
Abstracts which highlights the research in various disciplines from science and technology, business
and administration to social science and humanities. This research abstract issue features the abstracts
from 91 PhD doctorates who will receive their scrolls in this 86th UiTM momentous convocation
ceremony. This is a special year for the Institute of Graduate Studies where we are celebrating our
20th anniversary. The 20th anniversary is celebrated with pride with an increase in the number of PhD
graduates.
In this 86th convocation, the number of PhD graduates has increased by 30%
compared to the previous convocation. Each research produces an innovation
and this year, 91 research innovations have been successfully recognized to have
made contributions to the body of knowledge. This is in line with this year UiTM
theme that is “Inovasi Melonjak Persaingan Global (Innovation Soars Global
Competition)”.
Embarking on PhD research may not have been an easy decision for many of
you. It often comes at a point in life when the decision to further one’s studies
is challenged by the comfort of status quo. I would like it to be known that you
have most certainly done UiTM proud by journeying through the scholarly
world with its endless challenges and obstacles, and by persevering right
till the very end.
Again, congratulations to all PhD graduates. As you leave the university
as alumni we hope a new relationship will be fostered between you
and UiTM to ensure UiTM soars to greater heights. I wish you all the
best in your future endeavor. Keep UiTM close to your heart and be
our ambassadors wherever you go. / Prof Emeritus Dato’ Dr Hassan Said
Vice Chancellor
Universiti Teknologi MAR
Preventing premature convergence and proving the optimality in evolutionary algorithms
http://ea2013.inria.fr//proceedings.pdfInternational audienceEvolutionary Algorithms (EA) usually carry out an efficient exploration of the search-space, but get often trapped in local minima and do not prove the optimality of the solution. Interval-based techniques, on the other hand, yield a numerical proof of optimality of the solution. However, they may fail to converge within a reasonable time due to their inability to quickly compute a good approximation of the global minimum and their exponential complexity. The contribution of this paper is a hybrid algorithm called Charibde in which a particular EA, Differential Evolution, cooperates with a Branch and Bound algorithm endowed with interval propagation techniques. It prevents premature convergence toward local optima and outperforms both deterministic and stochastic existing approaches. We demonstrate its efficiency on a benchmark of highly multimodal problems, for which we provide previously unknown global minima and certification of optimality
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