2014
DOI: 10.1088/1367-2630/16/1/015026
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Swarming, schooling, milling: phase diagram of a data-driven fish school model

Abstract: We determine the basic phase diagram of the fish school model derived from data by Gautrais et al (2012 PLoS Comput. Biol. 8 e1002678), exploring its parameter space beyond the parameter values determined experimentally on groups of barred flagtails (Kuhlia mugil) swimming in a shallow tank. A modified model is studied alongside the original one, in which an additional frontal preference is introduced in the stimulus/response function to account for the angular weighting of interactions. Our study, mostly limi… Show more

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Cited by 186 publications
(206 citation statements)
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“…The turning interaction function is further supplemented by an additional prefactor (1 + cos θ ij ) which imparts an angular weighting on the turning interaction, maximised when the neighbour is directly in front with respect to the viewing angle of the focal fish. As described in [33,44], this extra position-dependence breaks the otherwise symmetric force response allowing for stable rotational (milling) and winding collective phases to emerge, producing qualitatively better fits to the group behaviour of small zebrafish shoals.…”
Section: Multi-agent Modelmentioning
confidence: 92%
See 1 more Smart Citation
“…The turning interaction function is further supplemented by an additional prefactor (1 + cos θ ij ) which imparts an angular weighting on the turning interaction, maximised when the neighbour is directly in front with respect to the viewing angle of the focal fish. As described in [33,44], this extra position-dependence breaks the otherwise symmetric force response allowing for stable rotational (milling) and winding collective phases to emerge, producing qualitatively better fits to the group behaviour of small zebrafish shoals.…”
Section: Multi-agent Modelmentioning
confidence: 92%
“…Our interaction model is adapted from the previous work of Gautrais et al [8] and subsequent modifications by Calovi and others in [33,44]. We derive a minimal model in which each contributing term, and associated parameters, are constrained by features observed directly from the experiment.…”
Section: Multi-agent Modelmentioning
confidence: 99%
“…In fact, most of these systems display both types of behavior, e.g. fish switch between migration and rotation (milling) [2,15], and, depending on environmental conditions, slime molds [6,16,17] and bacteria [18][19][20] will migrate or rotate. For example, the slime mold Dictyostelium discoideum (or Dicty) will collectively migrate if food is scarce, but transitions to a vortex to form a fruiting body as a last resort [21].…”
Section: Introductionmentioning
confidence: 99%
“…The instantaneous turn rate at time t is modeled by the mean reverting stochastic differential process (Gautrais et al, 2012;Calovi et al, 2014) …”
Section: Data-driven Simulationsmentioning
confidence: 99%
“…First, we demonstrate the ability to detect a leader in a synthetic dataset generated using a data-driven model (Gautrais et al, 2012;Calovi et al, 2014), in which the turn rate of each fish is described as a mean reverting diffusion process. Through our combined approach, we are successful in precisely isolating the leader from the rest of the group.…”
mentioning
confidence: 99%