On Hybrid Classical and Unconventional Computing for Guiding Collective Movement

2016 ◽  
pp. 561-590
Author(s):  
Jeff Jones
Keyword(s):  
Unconventional Computing ◽  
Collective Movement

scholarly journals Who directs group movement? Leader effort versus follower preference in stickleback fish of different personality

2016 ◽  
Vol 12 (5) ◽  
pp. 20160207 ◽  
Author(s):  
Shinnosuke Nakayama ◽  
Jennifer L. Harcourt ◽  
Rufus A. Johnstone ◽  
Andrea Manica
Keyword(s):  
Collective Movement ◽  
Group Movement ◽  
Focal Individual ◽  
Focal Fish ◽  
Set Up

During collective movement, bolder individuals often emerge as leaders. Here, we investigate whether this reflects a greater propensity of bold individuals to initiate movement, or a preference for shy individuals to follow a bolder leader. We set up trios of stickleback fish comprising a focal individual who was either bold or shy, and one other individual of each personality. We then recorded the movements of all individuals in and out of cover in a foraging context to determine how assiduously the focal fish followed the movements of each other partner. We found that a shy focal fish preferred to follow a leader whose personality matched its own, but we did not detect such a difference in bold fish. Despite this preference, however, the greater propensity of bold individuals to initiate movements out of cover meant that they successfully led more joint trips. Thus, when offered a choice of leaders, sticklebacks prefer to follow individuals whose personality matches their own, but bolder individuals may, nevertheless, be able to impose their leadership, even among shy followers, simply through greater effort.

SpatialRugs: A compact visualization of space and time for analyzing collective movement data

2021 ◽  
Author(s):  
Juri F. Buchmüller ◽  
Udo Schlegel ◽  
Eren Cakmak ◽  
Daniel A. Keim ◽  
Evanthia Dimara
Keyword(s):  
Collective Movement ◽  
Space And Time ◽  
Movement Data

Feedforward Micro-Extended-Analog-Computer Array

2012 ◽  
Vol 263-266 ◽  
pp. 1304-1309
Author(s):  
Jia Si Wang ◽  
Ying Zhang ◽  
Di Ming Ai ◽  
Feng Pan
Keyword(s):  
Research And Development ◽  
Pattern Classification ◽  
Numerical Experiments ◽  
Classification Problem ◽  
Analog Computer ◽  
Unconventional Computing ◽  
Particle Swarm Optimizer ◽  
Computing Model ◽  
Classic Pattern ◽  
Array Structure

The micro-Extended-Analog-Computater(uEAC) is a newly emergent unconventional computing model under research and development. Although, a single uEAC unit can achieve some classic pattern classification problem, the slop of the classification face generated by uEAC is a constant and moves parallely. So a feedforward array structure is proposed for the improvement of uEAC, and Particle Swarm Optimizer(PSO) is utilized to configure the uEAC array. The analysis of the mapping characteristics and numerical experiments both illustrate the effectiveness of the improvement.

scholarly journals Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Ariana Strandburg-Peshkin ◽  
Damien R Farine ◽  
Margaret C Crofoot ◽  
Iain D Couzin
Keyword(s):  
Group Structure ◽  
Spatial Scales ◽  
Group Living ◽  
Habitat Features ◽  
3 Dimensional ◽  
Collective Movement ◽  
Dimensional Reconstruction ◽  
Individual Decisions ◽  
Emergent Structure ◽  
Road Following

For group-living animals traveling through heterogeneous landscapes, collective movement can be influenced by both habitat structure and social interactions. Yet research in collective behavior has largely neglected habitat influences on movement. Here we integrate simultaneous, high-resolution, tracking of wild baboons within a troop with a 3-dimensional reconstruction of their habitat to identify key drivers of baboon movement. A previously unexplored social influence – baboons’ preference for locations that other troop members have recently traversed – is the most important predictor of individual movement decisions. Habitat is shown to influence movement over multiple spatial scales, from long-range attraction and repulsion from the troop’s sleeping site, to relatively local influences including road-following and a short-range avoidance of dense vegetation. Scaling to the collective level reveals a clear association between habitat features and the emergent structure of the group, highlighting the importance of habitat heterogeneity in shaping group coordination.

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