E-SWARM
Engineering Swarm Intelligence Systems
| Coordinatore | UNIVERSITE LIBRE DE BRUXELLES
Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie. |
| Nazionalità Coordinatore | Belgium [BE] |
| Totale costo | 2˙016˙000 € |
| EC contributo | 2˙016˙000 € |
| Programma | FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | ERC-2009-AdG |
| Funding Scheme | ERC-AG |
| Anno di inizio | 2010 |
| Periodo (anno-mese-giorno) | 2010-06-01 - 2015-05-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
UNIVERSITE LIBRE DE BRUXELLES
Organization address
address: Avenue Franklin Roosevelt 50 contact info |
BE (BRUXELLES) | hostInstitution | 2˙016˙000.00 |
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Obiettivo del progetto (Objective)
'Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In this project, we focus on the design and implementation of artificial swarm intelligence systems for the solution of complex problems. Our current understanding of how to use swarms of artificial agents largely relies on rules of thumb and intuition based on the experience of individual researchers. This is not sufficient for us to design swarm intelligence systems at the level of complexity required by many real-world applications, or to accurately predict the behavior of the systems we design. The goal of the E-SWARM is to develop a rigorous engineering methodology for the design and implementation of artificial swarm intelligence systems. We believe that in the future, swarm intelligence will be an important tool for researchers and engineers interested in solving certain classes of complex problems. To build the foundations of this discipline and to develop an appropriate methodology, we will proceed in parallel both at an abstract level and by tackling a number of challenging problems in selected research domains. The research domains we have chosen are optimization, robotics, networks, and data mining.'