Autonomous Recognition of Collective Behaviour in Robot Swarms

2020 ◽  
pp. 281-293
Author(s):  
Kathryn Kasmarik ◽  
Shadi Abpeikar ◽  
Md Mohiuddin Khan ◽  
Noha Khattab ◽  
Michael Barlow ◽  
...  
Keyword(s):  
Collective Behaviour ◽  
Robot Swarms

scholarly journals A Minimalistic Approach to Segregation in Robot Swarms

2019 ◽  
Author(s):  
Peter Mitrano ◽  
Jordan Burklund ◽  
Michael Giancola ◽  
Carlo Pinciroli
Keyword(s):  
Robot Swarms

Collective behaviour can stabilize ecosystems

2021 ◽  
Author(s):  
Benjamin D. Dalziel ◽  
Mark Novak ◽  
James R. Watson ◽  
Stephen P. Ellner
Keyword(s):  
Collective Behaviour

scholarly journals Fishing out collective memory of migratory schools

2014 ◽  
Vol 11 (95) ◽  
pp. 20140043 ◽  
Author(s):  
Giancarlo De Luca ◽  
Patrizio Mariani ◽  
Brian R. MacKenzie ◽  
Matteo Marsili
Keyword(s):  
Collective Memory ◽  
Large Scale ◽  
Group Formation ◽  
Individual Preference ◽  
Relative Number ◽  
Collective Behaviour ◽  
Control Group ◽  
Adaptive Networks ◽  
Modelling Framework ◽  
Migration Pathways

Animals form groups for many reasons, but there are costs and benefits associated with group formation. One of the benefits is collective memory. In groups on the move, social interactions play a crucial role in the cohesion and the ability to make consensus decisions. When migrating from spawning to feeding areas, fish schools need to retain a collective memory of the destination site over thousands of kilometres, and changes in group formation or individual preference can produce sudden changes in migration pathways. We propose a modelling framework, based on stochastic adaptive networks, that can reproduce this collective behaviour. We assume that three factors control group formation and school migration behaviour: the intensity of social interaction, the relative number of informed individuals and the strength of preference that informed individuals have for a particular migration area. We treat these factors independently and relate the individuals’ preferences to the experience and memory for certain migration sites. We demonstrate that removal of knowledgeable individuals or alteration of individual preference can produce rapid changes in group formation and collective behaviour. For example, intensive fishing targeting the migratory species and also their preferred prey can reduce both terms to a point at which migration to the destination sites is suddenly stopped. The conceptual approaches represented by our modelling framework may therefore be able to explain large-scale changes in fish migration and spatial distribution.

Measuring collective behaviour of multicellular ensembles: role of space-time scales

2008 ◽  
Vol 33 (2) ◽  
pp. 289-301 ◽  
Author(s):  
S. Rajesh ◽  
Somdatta Sinha
Keyword(s):  
Time Scales ◽  
Space Time ◽  
Collective Behaviour

COLLECTIVITY IN COMPOSITE FRAGMENT EMISSION FROM RELATIVISTIC HEAVY ION COLLISIONS

1987 ◽  
Vol 02 (10) ◽  
pp. 721-726 ◽  
Author(s):  
R. BOCK ◽  
G. CLAESSON ◽  
K. G. R. DOSS ◽  
R. L. FERGUSON ◽  
I. GAVRON ◽  
...  
Keyword(s):  
Heavy Ion Collisions ◽  
Heavy Ion ◽  
Collective Behaviour ◽  
Relativistic Heavy Ion Collisions ◽  
Ion Collisions ◽  
Plastic Ball

Composite fragments of 2 < Z < 10 have been measured in the Plastic Ball Spectrometer in 200 MeV/nucleon Au + Au and Au + Fe collisions. Strong azimuthal alignment of the fragments reveal the collective behaviour of the reaction.

From Swarms to Stars: Task Coverage in Robot Swarms with Connectivity Constraints

2018 ◽  
Author(s):  
Jacopo Panerati ◽  
Luca Gianoli ◽  
Carlo Pinciroli ◽  
Abdo Shabah ◽  
Gabriela Nicolescu ◽  
...  
Keyword(s):  
Robot Swarms
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