PERPLEXUS: Pervasive Computing Framework for Modeling Complex
Virtually-Unbounded Systems
Eduardo Sanchez, Andres Perez-Uribe, Andres Upegui, Yann Thoma
HEIG-VD, Switzerland
(eduardo.sanchez, andres.perez-uribe, andres.upegui, yann.thoma)@heig-vd.ch
Juan Manuel Moreno
UPC, Spain
moreno@eel.upc.edu
Alessandro Villa
UJF, France
avilla@neuroheuristic.org
Henri Volken
UNIL, Switzerland
henri.volken@unil.ch
Andrzej Napieralski
TUL, Poland
napier@dmcs.p.lodz.pl
Gilles Sassatelli
CNRS, France
sassatelli@lirmm.fr
Erwan Lavarec
Wany Robotics, France
lavarec@wanyrobotics.com
Abstract
This paper introduces Perplexus, a European project
that aims to develop a scalable hardware platform made of
custom reconfigurable devices endowed with bio-inspired
capabilities. This platform will enable the simulation of
large-scale complex systems and the study of emergent com-
plex behaviors in a virtually unbounded wireless network of
computing modules. The final infrastructure will be used
as a simulation tool for three applications: neurobiological
modeling, culture dissemination modeling, and cooperative
collective robotics. The Perplexus platform will provide a
novel modeling framework thanks to the pervasive nature
of the hardware platform, its bio-inspired capabilities, its
strong interaction with the environment, and its dynamic
topology.
1. Introduction
The Perplexus project aims to develop a scalable hard-
ware platform made of custom reconfigurable devices en-
dowed with bio-inspired capabilities that will enable the
simulation of large-scale complex systems [4] and the study
of emergent complex behaviors in a virtually unbounded
wireless network of computing modules. At the heart of
these ubiquitous computing modules (ubidules), we will use
a custom reconfigurable electronic device capable of imple-
menting bio-inspired mechanisms such as growth, learning,
and evolution. This ubidule bio-inspired chip (ubichip) [11]
will be associated to rich sensory elements and wireless
communication capabilities. Such an infrastructure will
provide several advantages compared to classical software
simulations: speed-up, an inherent real-time interaction
with the environment, self-organization capabilities, simu-
lation in the presence of uncertainty, and distributed multi-
scale simulations.
The strong interaction between our hardware infrastruc-
ture and the real environment circumvent the need to simu-
late the environment and ease the occurrence of unexpected
emergent phenomena. The observation of such emergent
phenomena will be now facilitated by the shorter simula-
tion time, brought by the hardware speed-up.
One of the major difficulties of a complex system simu-
lation is to define the structural organization of the modules
composing the model [4]. The self-organization and bio-
inspired capabilities of our platform will bring an innova-
tive solution to this problem: an evolving and hierarchical
structure. The function of each ubidule can be dynamically
and autonomously determined by the simulation itself: it
can be an independent agent or a part of a larger entity.
We have identified three domains where our model-
ing infrastructure will prove its usefulness as a powerful
and innovative simulation tool: neurobiological modeling,
culture dissemination modeling, and cooperative collective
robotics. We will perform qualitative and quantitative com-
parisons between classical implementations of these three
modeling applications and their implementation running on
a network of ubidules. For doing so, we envision three
strategic aspects to be addressed:
(1) Design and development of the hardware platform. It
will consist of a set of ubidules that will support the simu-
lation of our complex systems.
(2) Simulation of complex phenomena in the domains
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