Collective behavior in animal groups: Theoretical models and empirical studies

Giardina, Irene

doi:10.2976/1.2961038

Cited by 235 publications

(189 citation statements)

References 87 publications

Supporting

Mentioning

187

Contrasting

Order By: Relevance

“…The reader interested in the treatment of the problem by statistical physicists is referred to the reviews of Giardina [85] and Vicsek [86]. Tools initially developed for the study of out of equilibrium physical or chemical systems are adapted to the problem of living organisms.…”

Section: Statistical Physics Of Collective Motionmentioning

confidence: 99%

From behavioural analyses to models of collective motion in fish schools

et al. 2012

View full text Add to dashboard Cite

Fish schooling is a phenomenon of long-lasting interest in ethology and ecology, widely spread across taxa and ecological contexts, and has attracted much interest from statistical physics and theoretical biology as a case of self-organized behaviour. One topic of intense interest is the search of specific behavioural mechanisms at stake at the individual level and from which the school properties emerges. This is fundamental for understanding how selective pressure acting at the individual level promotes adaptive properties of schools and in trying to disambiguate functional properties from non-adaptive epiphenomena. Decades of studies on collective motion by means of individual-based modelling have allowed a qualitative understanding of the self-organization processes leading to collective properties at school level, and provided an insight into the behavioural mechanisms that result in coordinated motion. Here, we emphasize a set of paradigmatic modelling assumptions whose validity remains unclear, both from a behavioural point of view and in terms of quantitative agreement between model outcome and empirical data. We advocate for a specific and biologically oriented re-examination of these assumptions through experimental-based behavioural analysis and modelling.

show abstract

Section: Statistical Physics Of Collective Motionmentioning

confidence: 99%

From behavioural analyses to models of collective motion in fish schools

et al. 2012

View full text Add to dashboard Cite

show abstract

“…In the same way, the performances of sensor networks [6] can also be enhanced by the introduction of mobile agents [7,8]. In natural systems, on the other hand, mobile populations that coordinate through chemical or audible signals are obviously widespread, ranging from cell populations [9] to animal groups [10].…”

Section: Introductionmentioning

confidence: 99%

Consensus in networks of mobile communicating agents

Baronchelli

Dı́az-Guilera

2012

Phys. Rev. E

View full text Add to dashboard Cite

Populations of mobile and communicating agents describe a vast array of technological and natural systems, ranging from sensor networks to animal groups. Here, we investigate how a group-level agreement may emerge in the continuously evolving network defined by the local interactions of the moving individuals. We adopt a general scheme of motion in two dimensions and we let the individuals interact through the minimal naming game, a prototypical scheme to investigate social consensus. We distinguish different regimes of convergence determined by the emission range of the agents and by their mobility, and we identify the corresponding scaling behaviors of the consensus time. In the same way, we rationalize also the behavior of the maximum memory used during the convergence process, which determines the minimum cognitive/storage capacity needed by the individuals. Overall, we believe that the simple and general model presented in this paper can represent a helpful reference for a better understanding of the behavior of populations of mobile agents.

show abstract

“…The range of applications of such studies is indeed extensive [1,2,3,4,5,6,7]. As a matter of fact, coherent patterns of collective motion found in distinct families of biological species such as fish schools, flocks of birds, swarms of insects and even colonies of bacteria [6,5,8,1,4,9,10,11] have also been detected in granular matter systems, self-propelled particles with inelastic collisions and active Brownian particles in autonomous-motor groups [12,13,14,15,16,17,18,19,20,21,22]. Early in the study of such collectives, modeling and simulation have been recognized as playing a crucial role in gaining insight of the mechanisms underlying such an emergence of global features from a set of simple rules [23,24,25].…”

Section: Introductionmentioning

confidence: 99%

Emergence of coherent motion in aggregates of motile coupled maps

Ros

Antonopoulos

Basios

2011

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

In this paper we study the emergence of coherence in collective motion described by a system of interacting motiles endowed with an inner, adaptative, steering mechanism. By means of a nonlinear parametric coupling, the system elements are able to swing along the route to chaos. Thereby, each motile can display different types of behavior, i.e. from ordered to fully erratic motion, accordingly with its surrounding conditions. The appearance of patterns of collective motion is shown to be related to the emergence of interparticle synchronization and the degree of coherence of motion is quantified by means of a graph representation.The effects related to the density of particles and to interparticle distances are explored. It is shown that the higher degrees of coherence and group cohesion are attained when the system elements display a combination of ordered and chaotic behaviors, which emerges from a collective self-organization process.

show abstract

Collective behavior in animal groups: Theoretical models and empirical studies

Cited by 235 publications

References 87 publications

From behavioural analyses to models of collective motion in fish schools

From behavioural analyses to models of collective motion in fish schools

Consensus in networks of mobile communicating agents

Emergence of coherent motion in aggregates of motile coupled maps

Contact Info

Product

Resources

About