PERPLEXUS - Pervasive computing framework for modeling complex virtually-unbounded systems (FP6-IST) (2006-09-01 - 2009-08-31) (»add to infobox)

Eduardo SANCHEZ, Juan Manuel MORENO AROSTEGUI, Alessandro VILLA, Henri VOLKEN, Andrzej NAPIERALSKI, Gilles SASSATELLI, Erwann LAVAREC, N. N., N. N.

HAUTE ECOLE D'INGENIERIE ET DE GESTION DU CANTON DE VAUD (CH021 - Bern) (Switzerland), UNIVERSITAT POLITECNICA DE CATALUNYA (ES511 - Barcelona) (Spain), UNIVERSITE JOSEPH FOURIER GRENOBLE 1 (FR714 - Isère) (France), UNIVERSITY OF LAUSANNE (CH022 - Freiburg) (Switzerland), TECHNICAL UNIVERSITY OF LODZ (PL113 - Miasto Lodz) (Poland), CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) (FR101 - Paris) (France), WANY SA (FR813 - Hérault) (France), SCIPROM SARL (CH022 - Freiburg) (Switzerland), UNIVERSITE DE MONTPELLIER II (FR813 - Hérault) (France)

We will develop a scalable hardware platform made of custom reconfigurable devices endowed with bio-inspired capabilities that will enable the simulation of large-scale complex systems 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 implementing bio-inspired mechanisms such as growth, learning, and evolution. This reconfigurable circuit 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, simulation in the presence of uncertainty, and distributed multi-scale simulations. The strong interaction between our hardware infrastructure and the real environment circumvent the need to simulate the environment and ease the occurrence of unexpected emergent phenomena. The observation of such emergent phenomena will be now facilitated by the shorter simulation time, brought by the hardware speed-up. One of the major difficulties of a complex system simulation is to define the structural organization of the modules composing the model. The self-organization and bio-inspired capabilities of our platform will bring an innovative 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 largest entity. We have identified three domains where our modeling infrastructure will prove its usefulness as a powerful and innovative simulation tool: biologically-plausible developing neural networks modeling, culture dissemination modeling, and cooperative collective robotics modeling.

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