SWARM

Empirical analysis and theoretical modelling of self-organized collective behaviour in three-dimensions: from insect swarms and bird flocks to new schemes of distributed coordination

 Coordinatore CONSIGLIO NAZIONALE DELLE RICERCHE 

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 Nazionalità Coordinatore Italy [IT]
 Totale costo 1˙124˙000 €
 EC contributo 1˙124˙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-2010-StG_20091028
 Funding Scheme ERC-SG
 Anno di inizio 2010
 Periodo (anno-mese-giorno) 2010-11-01   -   2015-10-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    CONSIGLIO NAZIONALE DELLE RICERCHE

 Organization address address: Piazzale Aldo Moro 7
city: ROMA
postcode: 185

contact info
Titolo: Dr.
Nome: Irene Rosana
Cognome: Giardina
Email: send email
Telefono: +39 06 49937460
Fax: +39 06 49937440

IT (ROMA) hostInstitution 1˙124˙000.00

Mappa

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 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

self    swarm    collective    animal    theoretical    perform    individuals    organization    distributed    rules   

 Obiettivo del progetto (Objective)

'Animal groups represent paradigmatic cases of self-organized collective behaviour, where global coordination arises from local rules of interaction between individuals. A major issue, both for theoretical studies and technological applications, is to understand how self-organization emerges within a system with distributed intelligence. SWARM aims at providing new knowledge about self-organization and collective behaviour in 3D animal aggregations. To do that, SWARM will export concepts and methods from physics, and will integrate empirical work, data analysis and theoretical modelling. In particular, SWARM will: i) Perform field experiments on large insect swarms and bird flocks and retrieve individual 3D coordinates and trajectories. ii) Perform a statistical characterization of swarming/flocking behaviour; obtain information on the interactions between group members, and on the rules followed by individuals. iii) Develop empirically based models of 3D animal collective behaviour and design efficient, biologically inspired, algorithms of distributed coordination.'

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QUEST (2012)

Quantum Entanglement in Electronic Solid State Devices

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IPES (2012)

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SPACERADARPOLLINATOR (2014)

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